In spite of the fact that data scientists and data engineers have similar skill sets, they fulfil multiple job roles in the fields of Big Data and AI development systems. The data scientist fosters analytical models, while data engineers deploy those models under production. All things considered, data scientists primarily focus on analytics, whereas data engineers rely more vigorously on programming.

Top notch insights and management are significant components for utilizing data to its fullest potential. At EngineerBabu, the data scientist and data engineer work in harmony to streamline data presentation and strategy. We’ll walk you through the responsibilities and job roles of data scientist and data engineer, so you can figure out how to utilize data for your potential benefit. Let’s learn it in detail.

Data Scientist Vs Data Engineer: What They Do?

What is a Data Scientist?

A Data Scientist analyzes and interprets data to solve business related issues. At first, data scientists investigate data and perform market research to formulate business inquiries or questions based on a particular pattern or problem area. The data scientists should then design business questions as data analytics issues.

To recognize basic patterns in a data set, data scientists utilize advanced analytical technologies supported by statistics and machine learning. Data Scientists construct models to set up relationships between data objects. However, the Predictive models forecast future occasions dependent on previous existing records. While prescriptive models suggest significant changes in business strategy dependent on current and historical information.

Data Scientists should likewise interpret the consequences of their analysis to design data-driven business arrangements. At the point when data scientists present their discoveries to stakeholders, they should construct a cohesive narration that imparts the meaning of their results and how those results can advise business strategies.

What is a Data Engineer?

A data engineer can be represented as a data proficient who develops the data infrastructure for analysis. They are centered around the production status of data and things like resilience, formats, security, and scaling.

Data Engineers as a rule hail from a software engineering background and are capable in programming languages like Java, Scala, and Python. On the other hand, they may have a degree in math or statistics that assists them with applying diverse analytical approaches to deal with business issues. 

They are likewise knowledgeable about developing and managing distributed systems for the analysis of enormous volumes of data. Nonetheless, their essential target is to help data scientists transform a pool of data into important and actionable insights.

Data Scientist Vs Data Engineer: Role Requirements

What Are the Requirements for a Data Scientist?

Data Scientists should be acquainted with the accompanying programming languages: 

• Python
• R
• Java
• MATLAB
• Scala
• C
• SQL

In light of current requirements, this is what you’ll have to get a regular mid-level work: 

• Master’s Degree or Ph.D. in Computer Science, Math, Engineering or a relevant quantitative field.
• At least five years of experience in an Analytics or Data Science Job role.
• Excellent proficiency in SQL.
• Working experience with Java and Python.
• Good Analytical and mathematical skills.
• Experience in Data Mining methods.
• Knowledge on advanced statistical concepts and methods.
• Hands-on knowledge of  Predictive Modeling Algorithms and frameworks.
• Working experience with Machine Learning techniques (such as, artificial neural networks, decision tree learning, and clustering).
• Experience in creating automated work processes (Python or R).
• Experience in using web services like DigitalOcean, Redshift, Spark, and S3.
• Experimental designing experience and A/B testing.
• Experience in visualizing and presenting data utilizing Business Objects, Periscope, ggplot, and D3.
• Experience working in a cloud system with huge data sets.
• Proven working experience in Hadoop.
• Experience with both Relational Database and NoSQL Database (for instance, Couch, MongoDB, and Neo4J).
• Good understanding of architecture and system integration.
• Experience in data analysis from third-party suppliers like AdWords, Google Analytics, Facebook Insights, and Hexagon.

What Are the Requirements for a Data Engineer?

Data Engineers need to know the accompanying programming languages: 

• Python
• Java
• C++
• Scala

In light of current requirements, this is what you’ll require to get the data engineer designation:

• Bachelor Degree in Statistics, Computer Science, Information System, or another relevant quantitative field.
• Minimum five years of professional experience or a Masters Degree with minimum three years of experience.
• Advanced working knowledge on SQL (composing and troubleshooting).
• Experience working with query composing, relational database, and knowledge over other databases.
• Experience managing, developing, and optimizing big data models and pipelines.
• Working experience with PostgreSQL, MongoDB, and Redis.
• Experience performing inner and outer root cause analysis.
• Strong analytical skills while working with unstructured data sets.
• Cloud-based data solution working experience (e.g., AWS, EC2, EMR, RDS, and Redshift).
• Proven work experience in effectively processing, manipulating, and extracting values from huge and disconnected data sets.
• Working experience on Bash Scripting or JavaScript or both.
• Excellent Project and Organization Management Skills.
• Experience with configuration and automation management.
• Working knowledge of code and scripts (for instance, Java, JavaScript, bash, and Python).
• System Monitoring, alert, and dashboard experience.
• Hands-on experience with tools like Hadoop, Kafka, and Spark.

Difference Between Data Scientist and Data Engineer

Taking everything into account, there are many similarities between a data scientist and data engineer. The thing that makes them different is what they are focused on. How about we investigate the principle difference between both i.e., data scientist vs data engineer:

A. Data Engineer: A data engineer’s objectives are more centered around tasks and development. They are liable for building automated systems and model data structures to work with data processing. Subsequently, their goal is to develop and create data pipelines and tables to help data customers and analytical dashboards. 

Data Scientist: On the other hand, data scientists are more focused on the queries. They need to ask and answer queries in order to minimize the overall expenses, increase profit, and improve customer experiences. Accordingly, data scientists gather support, analyze, and propose a conclusion to the inquiry or question. Some of the frequent inquiries that are faced, includes:

• What sort of advertisements would get the customer to buy something? 
• Is there a speedier way for package delivery?
• What impacts patient readmission?

B. Data Engineer: Evidently, both data engineer and data scientist usually rely on SQL and Python. Despite that, the tech jobs vary a lot for both data engineers and data scientists. Data Scientists use libraries like Pandas and SciKit Learn. Whereas, data engineers use Python to manage pipelines. Libraries like Airflow and Luigi are valuable in such a manner. 

Data Scientist: The questions of data scientists are more centered around ad-hoc. Data engineer questions are directed towards data transformation and cleaning up. The Data Scientists use tech-tools like Jupyter Notebook, Tableau, and so on.

C. Data Engineer: With respect to background, both data engineers and data scientists are needed to have a specific level of understanding for data and programming. Whereas, there are a few differences that surpass programming.

Data Scientist: Since data scientists are more similar to analysts, having a research-based foundation is an advantage. This could be in anything going from financial aspects to psychology to epidemiology, or anything as. As far as skills are concerned, data scientists ought to have a blend of SQL and Python experience along with a good business sense.

Wrapping Up

Despite the profession you choose, it will be fundamental to equip yourself with advanced degrees and certifications. All things considered, more organizations are acknowledging the worth of alternative education.

While there is some crossover when it is about required skills and job role responsibilities. These are not a type of interchangeable jobs. So you’ll need to make a firm decision and have some expertise in either. In any case, both positions have an amazingly positive and rewarding job outlook.

However, if you like to explore both data science and data engineering, then, at that point, you could look for a career in Machine learning. The Machine Learning Engineers are capable in both data science and data engineering and have sufficient knowledge and experience to work in both fields.

If you are looking to hire such experts then EngineerBabu is the right place for you. We are an experienced team of data scientists and data engineers to support our clients in taking their business to the next level. For any query or assistance, you can reach out to us and hire expert data scientists and data engineers or a machine learning engineer. 

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There is an extreme demand for AI and Machine Learning experts who are adequately qualified to do cutting edge exploration and designing. Simultaneously, the inventory of specific Machine Learning ability is scant – however the circumstance is progressively further developing because of the new Master’s and Ph.D. programs in ML that have been introduced all around the world over the last couple of years.

All things considered, to hire Machine Learning experts is a difficult errand for talent recruiters. It is not only due to the shortage of ML ability yet additionally because of an absence of significant experience among recruiting professionals.

Why Hire Machine Learning Experts?

Machine Learning is the most common way of empowering computers to perform tasks that have until as of late, been completed performed by humans.

Before the introduction of machine learning, computer systems and software’s just knew the data that a programmer releases. The outcome is a software system that can’t innovate, and that must be provided orders to function.

To hire Machine Learning engineers, it permits organizations to change huge data sets into statistical information and actionable knowledge. This important information can be integrated into everyday business processes and operational activities to react to changing business demands or business conditions. Beside automation repeatable tasks, organizations around the world use Machine Learning to assist with business operations and scalability.

As machines have a wider scope of data processing ability than humans. It is feasible for them to organize and scan data more rapidly than any individual can. It not only creates more valuable software as well as more effective software programming.

This is really relevant to a recruiting manager without a strong technical background. It’s their job to choose if a candidate has the right Machine Learning abilities that are important to be successful. So, let’s dive somewhat more profound into machine learning experts and the most ideal approaches to hire machine learning experts.

Required Skills To Hire Machine Learning Engineers

1. Specialized Skills Required

The main expertise needed for such engineers is that they should have full-fledged specialized information on coding/programming to deal with such ventures. Here you need to check the specialized capacity of the applicant and do the coding test to ensure he/she is qualified to manage ML model development. To assess their specialized skills, additionally guarantee you have the experienced candidate to hire the right machine learning engineer.

2. Interactive Communication Skills

Another significant factor that should be thought of to hire Machine Learning experts is communication skills that are imperative to communicate with their colleagues. The ML engineer should agree on a communication framework with an organization prior to starting the project. In case you are more stressed over the communication boundaries you need to check this ability to enable the smooth communication process.

3. Creativity with Cognitive State of Mind

A ML expert’s mind ought to be adequately creative enough to comprehend your imagination towards a dream AI project. You need to make different inquiries about how much they are interested or enthusiastic about working on such projects. Their creative minds can just foster a unique model that can give an edge to your business. Whereas, simultaneously gives a chance to them to use their creative thinking in developing the more creative applications for your business.

4. Easily Adaptive to New Technologies

Technology is one the most advanced fields where new developments occur globally. Likewise, ML is also a continually developing field taken on by the new technologies everyday. Thus, while aiming to hire machine learning engineers should have the ability to adapt to such new technologies. He should always be updated with new evolving technologies and keep adjusting to the industry trends and execute it with the right solution in today’s environment.

5. Work with Detailed Deliverable Goals

To achieve the AI or ML projects, engineers need to divide the assignments into more modest deliverable objectives. A detailed plan outline for getting the specific steps that assists with building a significant model. Introducing detailed and deliverable objectives are particularly crucial to make the accurate decision and evaluate the project for best performance.

How can an IT Recruiter Hire Machine Learning Expert?

The execution of Machine Learning basically implies a system is presently not restricted by the software engineers’ humanly vision. Presently, a machine can learn its own strategies through new and inventive cycles that developers or analysts might not have even thought about.

However, it is exceptionally helpful in light of the fact that it permits developers to design software with a particular objective, without focusing on the whole process of how it does as such.

Discovering approaches of computer programming to interpret such immense amounts of data has become challenging for even the best engineers to execute. The ML takes into consideration the formation of methodologies beyond human foresight and planning.

Resources/Tools/Technologies for Machine Learning

There are a ton of tools available for Machine Learning experts and are accessible in the Python language, while R is less common. Some Deep Learning systems are accessible in C++ or Java, because it is quicker and more memory-effective than Python. In Python, the most famous libraries incorporate Pandas, Scikit-learn, TensorFlow, and PyTorch.

Skills and Techniques A Machine Learning Engineer Familiar With

An effective AI specialist ought to have extraordinary mathematical skills. Likewise, they should be specialists in both programming and statistics. Thus, they can utilize their problem solving abilities to have a depth of information on Machine Learning models. Without a doubt, the machine learning engineers prefer Python over any other language.

Hire Right Machine Learning Expert for a Successful Project

You can’t recruit substandard developers and anticipate top quality results. You likewise can’t recruit the ideal individuals without redesigning the workflow. It is crucial to create harmony between Machine Learning experts and the workflow of machine learning programs they are working with.

A great deal of energy is spent to hire machine learning engineers for the project. While they are significant, they can’t work without the right analysts, engineers, or strategists. The target of these job roles are not clearly visible with respect to the data scientists.

Thus, before you enter any ML project, assembling the right talent is fundamental for guaranteeing the success of your venture. Machine learning experts administrations are majorly in demand as enterprises look to adapt it for improving their growth.

EngineerBabu provides high-end dedicated Machine Learning solution providers to assist your organization or projects with digital alteration. For any query or guidance, contact us and hire machine learning expert. We are here to help you in scaling your business venture in this competitive market with a guided direction.

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We at EngineerBabu, are committed to helping enterprises of every scale hire remote engineering teams and manage them seamlessly and at an affordable cost. Over the years, we have gathered some really useful tips under our sleeves that can make hiring remote engineering teams and managing them easy. In this article, we will share some of the most important tips on the subject, read on.

Why Hire a Remote Engineering Team?

While remote working has become the new normal, the cost of hiring, managing, and maintaining an in-house remote team has gone up. According to a Forbes article, the cloud costs for enterprises rose by 30% in 2020 compared to last year. Apart from the cost factor, there is a major time factor involved. Hiring a full-time engineer can take anything in between 3-6 months. Extrapolate this to hiring an entire engineering team, the effort and time will be immense. Additionally, the cost of maintaining and training the team – to keep up with the evolving technologies, can make the entire process time and cost-intensive. At EngineerBabu, our mission is to help enterprises hire remote engineering teams at affordable costs across domains and technologies. 

Over the years we have worked with 5000+ founders, 484+ clients, and delivered almost 1000 projects. Working with remote engineering teams can be different from having a full-time in-house team. Especially for enterprises that haven’t done this before. In the subsequent section of this article, we will share the best practices of hiring and managing remote engineering teams.

Best Practices to Hire Remote Engineering Teams

1. Plan Ahead

The world of software engineering is going Agile and iterative. But the same principles may not help while hiring a remote engineering team. If you are building a team from scratch for product development, you must plan ahead. Making a note of the below pointers, before you embark on the journey of hiring a remote engineering team can be helpful.

• Plan the major milestones you would want to achieve and create a roadmap.
• Plan for the technical skills that you would need in the team to achieve your product goal. Not just in the current scenario, but in the future too.
• The number of team members you would need – and the seniority.
• Plan for the skills gap – in case you are augmenting your current team – see the skills gaps that you have in the existing team and then plan to hire a remote engineering team accordingly.

2. Choose the Right Outsourcing Partner

Hiring remote engineering teams is becoming the new normal and so is the proliferation of outsourcing partners. Here are some things to consider while choosing an outsourcing partner:

a. Long-term Partnership

Once you hire a remote engineering team, they will work with you for months and maybe years altogether. It will be important to choose a service provider who can provide long-term product support, helps you plan, and is ready for contingencies. Precisely why, it will be important to look for a partner and not just a provider. Your service provider’s job doesn’t end at building a remote engineering team for your enterprise but seeing the project through.

b. Expertise

While hiring a remote engineering team, it will be important to partner with a service provider that isn’t a one-stop shop for all kinds of remote workers, rather has expertise in helping enterprises hire remote engineering teams across domains and technologies.

c. Compatibility

It will be critical to answer this question – does your outsourcing partner understand your goals and objectives and is passionate about delivering them? It is important that your outsourcing partner is aligned with your enterprise’s objectives, for them to help you hire an engineering remote team. At EngineerBabu, our skilled engineers believe in aligning with your company’s goals to provide expertise for a perfect synergy.

d. Accountability

Other important factors to assess will be – How do they vet the teams, what is their selection process, how do they plan to keep up should you want to augment the team with evolving technology skills, etc.? At EngineerBabu, our engineers are carefully handpicked after a rigorous selection process. Every engineer that we have in our team has two attributes in common. These are, passion for engineering and dedication to deliver on time.

e. Time, Cost, and Effort Required

The choice of the outsourcing partner to hire a remote engineering team will also depend on how soon you want to get started. That will also mean choosing a partner who is fast but does not compromise with quality. For instance, our team has engineers who are Crème de la crème engineers, and our swift process can help you hire a remote engineering team and get started with your project within a week. Another important factor will be to consider the cost of hiring an outsourcing partner. Needless to say, it makes sense partner with an affordable service provider for your enterprise in the long run.

Managing a Remote Engineering Team

Hiring a remote engineering team is just half the battle won, for the success of your project it will be important to manage them efficiently as well. One of the most important aspects to remember while managing a remote engineering team is that a remote engineering team is an extension of your in-house team, whether they are or aren’t on your payroll. Hence, the way you work with a remote engineering team should be similar to how you work with in-house team. It will help build team spirit and strengthen their dedication. Some tips to consider to successfully manage remote engineering are –

1. Communicate

Treating and communicating with your remote engineering team as you would do with a full-time team is important. More often, project managers end up under-communicating with remote teams. It can lead to the team not feeling a part of the bigger goal. Therefore, keeping the remote engineering teams involved in the bigger picture by sharing with them the product roadmap, important milestones that you want to achieve, and most importantly the bigger mission of your product or enterprise will make a great deal of difference. Use a channel like Slack to continuously be in touch.

2. Scrums and Daily Stand-ups

Like any engineering project, scrums and daily stand-ups are important to track the progress of projects, discuss challenges and further steps. Usually, PMs tend to delegate a portion of the project to the remote engineering teams and take weekly updates. It can be counterproductive since any issues or delays will come up only during the weekly updates. Additionally, since the remote engineering team will work hand-in-hand with your full-time team, a daily scrum/stand-up will help them collaborate better.

3. Make the Best Use of Project Management Tools

Use project management tools like JIRA or Hive to plan, manage and track projects. Project management tools can go a long way in planning and to prepare for contingencies as well.

4. Be Agile

Be flexible and Agile enough to tackle any unexpected issues coming your way. The tech world is evolving, so are your product ideas. From idea to implementation, the product will improve as your plan changes. Thus, it will be crucial to consider when you hire a remote engineering team to ensure that team gets communicated with any required modification. Likewise, choosing the right outsourcing partner will become crucial. They will help you adapt to evolving needs by augmenting the team with engineers. Along with the required skill-sets or quickly increasing the team size when needed.

Wrapping Up

Remote work has become the new normal. Many companies plan to shift to a remote working model even post-pandemic. Team augmentation by hiring remote engineers was already being adopted by the IT industry and tech startups. The need and benefits of hiring a remote engineering team have become even more evident in a post-pandemic world. Hiring a remote engineering team can mean – higher productivity with huge time and cost savings. We hope this article will help you in hiring and managing a remote engineering team. However, at EngineerBabu, we partner with enterprises across domains and scale. We help them to build best-in-class engineering teams for crafting a successful product. If you are looking to hire a remote engineering team and want to know more about our services – connect with us.

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With integration of Machine Learning into mobile applications, the organizations can likewise further improve their business sales by making futuristic and intelligent decisions. Since the innovation renders countless advantages to businesses, the demand for Machine Learning integration into existing applications and making ML-supported applications is increasing at an extraordinary rate.

The ML engineers build applications that support machines to learn from their past information or data, examples, and patterns without any precise programming structure. Thus, it isn’t simply learning. Machine Learning is about listening, understanding, and learning by using human efforts to the machine. What’s more, to develop these systems, know the top attributes of a Machine Learning Engineer.

So, let’s learn in detail about what is Artificial Intelligence, Machine Learning, and how to hire a Machine Learning Engineer?

What is Artificial Intelligence (AI)?

Artificial Intelligence is a collection of various technologies working together to empower machines to sense, understand, act, and learn with a human-like level of intelligence. Possibly that is the reason it appears to be like everyone’s meaning of AI is different. However, Artificial Intelligence isn’t only a certain thing.

Technologies, such as ML and NLP (Natural Language Processing) are all parts of AI technology. Everyone is advancing along its own way and, when applied with data, automation, and analytics, can assist businesses to accomplish their objectives, whether it is developing customer care or enhancing the supply chain.

The AI algorithms are intended to make decisions, regularly using real-time data. They are like inactive machines that are only appropriate for mechanical or pre-determined reactions. Using sensors, computerized data, or remote inputs, the information is combined from a wide range of sources, analyzes the material in a split second, and acts over the derived output from those data or information. It is deliberately designed by humans and arrives at a conclusion depending on their instant analysis.

What is Machine Learning (ML)?

Machine Learning is a subsidiary or we say, an application of AI that gives systems the ability to learn automatically and improve with experience without being specifically programmed. ML focuses on computer program development that can access information and use it to learn on their own. 

The most common way of learning starts with data observation, like direct insight, or guidance, to look for some patterns in data and make better and futuristic decisions. The major perspective is to allow the computer system to learn automatically i.e., without human assistance or guidance and define activities accordingly.

It is important to hire a Machine Learning engineer because it gives businesses a perspective or pattern on customer behavior and business operations, in addition to that supports new products development. A lot of leading organizations, like Uber, Facebook, and Google make ML a focal point of their operations. Thus, Machine Learning has turned into a huge competitive differentiator for many organizations.

How to Hire A Machine Learning Engineer?

If the company is spending on Artificial Intelligence and Machine Learning development, then it is recommended to be very careful when you hire a Machine Learning Engineer or AI expert, who can be a great asset for your company. Hence, there are few important points to consider when you aim to hire a Machine Learning engineer or Machine Learning experts. Below we have mentioned in detail what you need to look at when you hire a Machine Learning engineer.

1. Technical Skills

The main expertise needed for such engineers is that s/he should have full-fledged technical expertise coding/programming to chip away at such tasks. Here you need to ensure the technical specialization of the applicant and do the coding test to verify s/he is qualified to manage AI and ML model development. To assess their technical abilities, likewise ensure you have the accomplished experts to recruit the right candidate.

There are various programming languages and frameworks that you need to test the expertise of to hire a machine learning engineer. These are as follows;

a. Python

The programming language expertise is fundamental to perform ML algorithms. You need to ensure that the candidate is aware of all the accessible features in the language. 

b. Pytorch/TensorFlow

There are two deep learning frameworks that overwhelm the ML market. TensorFlow is simpler to use for deployment while Pytorch is appropriate for experimentation. Ensure that the candidate must possess hands-on experience of both.

c. Scikit-learn

This is the most exemplary ML algorithm. Mastery in Scikit will help in solving many small-data problems.

d. NumPy and Pandas

While working with data, select precisely in what data you are interested. Hire a Machine Learning engineer who uses NumPy for basic functionality and Pandas for complex.

e. Apache Spark

Apache Spark enormously speeds-up the development efforts. Machine Language developers should be familiar with Apache Spark.

2. Interactive Communication Skills

Another significant factor should be considered while aiming to hire a Machine Learning Engineer is their communication abilities, which is essential to coordinate with their colleagues. AI and Machine Learning experts should agree on following a communication framework with the organization before starting the project. Hence, in case you are worried about the communication skills, you need to check the ability in the candidate to ensure a smooth communication process.

3. Curious, Creative, and Adaptable with New Technologies

The venture for which you are looking to hire a Machine Learning Engineer and an AI expert should spark their creative mind and ignite their imagination. They ought to fire a number of questions and you should feel motivated by their passion for the project and quality deliverables. AI and Machine Learning expert have to make their path and dedicated effort to understand why they are developing or improving something. Thus, they can put forward recommendations that are significantly valuable for the project.

After being curious and creative, a machine learning expert should have to be adaptable to new technologies. As evidently, change is the only constant in life, and that has never been more genuine than today in innovation. Artificial Intelligence and Machine Learning are continuously growing fields with new technologies and sectors getting introduced each day. Your AI and Machine Learning experts should regularly update with shifts in technology and adapt to industries evolving patterns to execute apt solutions that work in the current situation.

4. Set Detailed and Deliverable Goals

To complete the AI or ML projects, engineers need to divide the tasks into more modest deliverable goals. A detail plan is presented for getting the specific steps which support in building a significant model. Laying out detailed and deliverable goals are crucial to make the right choice. Yet, evaluate the project working for its best performance.

Cost to Hire a Machine Learning Engineer

To calculate how much does it costs to hire a machine learning engineer, here is a useful guide to note:

a. Plan and Analysis

At this stage, you need to unmistakably state what software you need to make, what issues it will resolve, and what benefits it will offer to clients. During this phase, you can plan all the required development stage. Furthermore, compute the estimated cost for software development and deployment.

b. Prototype Development & Evaluation

Regularly, these costs about $25,000 for complex project ventures. In any case, it essentially relies upon the complexity of the software to build. Therefore, these charges may vary i.e., less or more. 

c. Minimum Viable Product (MVP)

MVP is an original product that contains the least number of features and functions for the planned functionality. Then, the MVP is handed to a group of users who test it and give their feedback to build the improved version of the final outcome. Thus, you can get accurate feedback during the development phase and can remove/improve/modify something to address the genuine needs of clients. MVP development cost begins from $25,000 to $100,000 and even more sometimes.

d. Product Launch

Generally, we calculate the last stage expense in the start. Thus, it almost present the required definite expenses for planning and deploying the final product. However, to prepare that the prototype and MVP development can bring about greater numbers.

Overall, the minimum development cost of AI-based software developed by top artificial intelligence companies ranges from $5,000 to $100,000. The expense relies upon the project complexity, industry, development time, applicability, and numerous other factors. Discussing what amount does it cost to develop an AI or machine learning software for each driving industry. Below is the following result;

Computer Software: 50,000+; Financial Services: 30,000+; Information Technology & Services: 25,000+; Healthcare: 25,000+; Education: 15,000+; Research & Development: 10,000+; Web & Mobile Applications: 10,000+.

Wrapping Up

Hiring a right AI or Machine Learning expert would be a troublesome and time taking process as well. It includes basic stages of vacancy detail with an exact set of responsibilities, to avoid the confusion between data analyst, data scientist, and machine learning engineer. Thus, it requires thorough understanding of technology and expertise to hire a machine learning engineer who is expert in his task. So, to get a reliable and expert engineer, you can hire a Machine Learning engineer from EngineerBabu and for any other query or information you can contact us. We are an expert team of developers and engineers that are excellent in their deliverables and client satisfaction.

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WordPress is currently one of the most popular and biggest Content Management Systems in the world. It is used for building personal blogs to most creative and interactive websites. Hence, there are 55,000+ plugins and more than 31,000 themes available for WordPress Developers to make best customized WordPress development. This makes WordPress the number one choice among developers and businesses to build websites or blogs.

These statistics depict there is no shortage of WordPress developers around the world. So, the question arises, how to hire a WordPress developer from the sea of talent, and what to look for while outsourcing WordPress development? Let’s try to answer such questions and learn how to hire a WordPress developer.

When to Hire A WordPress Developer?

Basically, a WordPress developer in a tech-architect, or someone who develops or supports the development of a WordPress website. The developer suggests or introduces new ideas that are feasible with the respective business. Such developers also help in implementing and setting up accurate solutions, as well as integrating and modifying the things to near perfection. 

Apart from that, a skilled WordPress developer can also suggest and guide you in the best way to implement the best strategies that can meet your needs. Such as, customized coding, installing premium plugins, etc. based on your needs. 

To make an SEO friendly website, they can also guide to use relevant ready-made templates, customize UI and UX and guide designers in doing so. Overall, a good WordPress developer is one who understands when the product requires customization and when not; just make what is required, not too much or less. 

A clever WordPress developer can also suggest measures to minimize your expenses and without any custom coding. For instance, using the readymade premium plugins and code combination. If the developer is visionary and a good architect, then will definitely suggest the optimal ways to accomplish any business goals.

Advantages of Hiring A WordPress Developer

• Less time in learning the intricate details of your WordPress development website.
• The developer can actually add customized functionalities to your site, which is helpful in the event when you require specific features and choices. 
• There are minimum chances that your site will look ‘cookie cutter’.
• Your WP developer will realize how to capitalize on the platform, which means boosting your site’s performance, security, etc. 
• You’ll have somebody to reach out for assistance with specialized technical issues, bug fixing, updations, and many more.

How to Hire A WordPress Developer?

While looking to hire a skilled WordPress developer, then it is important to understand that it is your responsibility to set the quality of developer and thoroughly search your candidate on various portals. If you fail to do so, then you will end up wasting your time and resources or might have to satisfy with a sub-par job or object. Thus, following these 4 steps thoroughly you can find the answer of how to hire a WordPress developer.

Step 1- Define your Requirements Accurately

Regardless of whether you are not building your site personally, you’ll require a clear idea of your requirements before you hire a WordPress developer. The more explicit details you can provide, the better the final product is going to be. 

You don’t have to begin arranging the format of your site, however you will need to define its purpose and content in a more broad manner. For example, consider:

• What will be the objective of your site– to share data, build a community, make sales, and so forth.
• The types and number of pages you would prefer.
• Any specific features and functionality your site requires, like booking or order forms, social media integration, e-commerce facility, calendars, etc.

When you hire a WordPress developer, these are the initial data briefs you’ll need to convey to them. Thus, you’ll know you both are working on the same page about the direction your website requires.

Step 2- Know what you are looking for in a WordPress Developer

In case you’re aiming to hire a WordPress developer, you’ll need to realize how to evaluate applicants. It can be difficult, particularly when you have minimal technical specialization. However, you can still make an informed decision.

To make it possible, you’ll need to consider the below mentioned factors:

• What are the charges of WordPress Developer? 

Specifically, be careful about those on the exceptionally low end of the scale, charging $5 to $15 each hour (or something like that). This probably demonstrates the lack of experience.

• Do they have previous work Portfolios?

Everything you can manage while checking a potential recruit is to take a look at previous websites or products they worked upon. If possible, then visit the sites and invest a little time on them, test how easy or difficult it is to navigate the site, whether the key elements work appropriately or not, etc.

• Can you get some References, Reviews, or Testimonials? 

Try to reach out to their colleagues or bosses they earlier worked for, and ask what their experience resembled.

• What tools do they use?

A few designers can even develop a custom WordPress development theme, whereas others can effectively use page builder plugins like Elementor. There’s not actually a set in stone here, yet you’ll need to know precisely what the establishment of your site will be on the grounds that it will influence how you will implement changes in the future.

At last, it’s wise to connect and have a discussion with the strongest applicants prior to settling on a decision. Get some information about their experience, let them realize what you’re searching for, etc. This will disclose to you a couple of things – how fast the designer responds, how well they communicate, and how clearly they understand your needs.

Step 3- Inspect their Portfolio In-depth

Designers ought to provide a portfolio of their recently finished ventures. Here are only a couple of things you should be looking for:

• Worked on Similar Projects to your Business

You need to identify that the designer is fit for delivering what you are requesting or to serve the purpose accurately for what you are hiring a WordPress developer.

• Skill Level

While hard to pass judgment, in the event that you have a complex project that requires multiple functionality, it’s significant that the hired developer has the experience to build it. If their portfolio contains most of the simple sites with restricted functionality, they presumably don’t have the expertise to fulfil your project demands.

• Types of Projects

Assuming you need a custom plugin, yet the developer just builds websites, or the other way around, they might not have the skills you need.

Step 4- Conduct Video Interview to Hire A WordPress Developer

As video meets interviews commonly start communication in the hiring process, use them to ask some fundamental queries about the job role and a candidate’s fit. Useful questions might include: 

• For what reason do you feel you’re ideal for this position?
• What pulled you to working with our organization?
• What specialized WordPress development technical skills do you have?
• Clarify how your schooling and qualifications will work well for you in this job role.

The Interview Questions to ask While Interviewing A WordPress Developer

In the wake of narrowing down your contender to a chosen handful. It’s an ideal opportunity to investigate each candidate in more depth.

To test potential skills of a WordPress developer while recruitment. Ask them a progression of questions that plunge deeper into what they guarantee they can do. Here are a few questions you might jump at the chance to pose:

• What is your experience of customizing or writing WordPress development code?
• Which WordPress plugin do you use frequently?
• What is a custom theme?
• What is your experience of making new themes in WordPress development?
• How would you normally optimize a site for SEO?
• What are your preferred communication strategies?

What are the Best Ability Tests to Hire a WordPress Developer? 

• CSS: The CSS developer test checks applicant knowledge and skills in CSS techniques and concepts.
• WordPress Developer: Evaluates applicants knowledge in the WordPress infrastructure along with coding abilities.
• PHP (Coding) at Intermediate-Level Algorithms: The PHP test evaluates coding abilities of applicants with a short coding assignment.
• SQL (Coding) at Intermediate-Level Querying: The SQL query running test checks candidates abilities in making a query on the database with medium-level complexity.
• PHP (Coding)Entry-Level Algorithm: This PHP test evaluates the applicant’s ability to program a small algorithm and tests their basic programming skills.
• PHP (Coding) Object-Oriented Programming: This PHP coding test estimates the applicant’s object-oriented programming abilities and skills to use  PHP’s specific functionalities.
• Critical Thinking: The critical thinking test assesses an applicant’s ability to implement critical thinking skills to ensure problem’s solution.

How much does it Cost to Hire a WordPress Developer?

When aiming to hire a WordPress developer, the first question always arises is; What is the normal hourly rate or the annual salary of a freelancer or a full-time employee? Thus, on an average the yearly compensation of a skilled WordPress developer is $112,921. Whereas, most freelance developers charge between $60-$100 each hour.

Other than the yearly salary or hourly payment of both employees and freelancers, make certain to factor in the cash you need to spend. While, preparing and onboarding another WordPress developer. A full-time employee normally costs more. As you need to prepare them to find a place with your organization culture and locally available to them for your method of chipping away at projects. On the other hand, a freelancer will introduce their own process and commonly require less oversight and expenses.

Wrapping Up

Hiring a WordPress Developer can be like exploring a minefield the first occasion when you do it. Yet each time you work with another developer you will find the interaction process becomes simpler. There’s a ton to consider, from scope of project and contracts to onboard candidates and payments.

The WordPress developers introduce a host of benefits to a company, such as ongoing technical support and advanced feedback into the user experience and technical SEO issues. Hope, reading this blog helps you in answering your question of how to hire a WordPress developer.

So, if you also like to hire a specialized WordPress developer then EngineerBabu is the right destination for you. We understand business needs and dedicatedly work to deliver best services and quality business solutions. For more information and detail you can Contact Us, we are here to help you in the best possible way we can.

The post How To Hire A WordPress Developer? appeared first on EngineerBabu Blog.

Business Intelligence is a very wide term used to cite technologies and applications. Both are thoroughly used in collecting, analyzing, and presenting business details and information. The demand and worth of BI has increased gradually after the worth of data gathering and analysis is valued. As a result, spreadsheet maintenance has become an age old activity against actionable and insightful data visualization and interactive business dashboards.

After the COVID-19 impact all over the world, the year 2020 particularly became a major opportunity for the BI trends and the industry. Hence, last year business intelligence trends will continue to play out through 2021. However, the BI market is evolving rapidly. Thus, is the high time to monitor the trends of business intelligence and work over it. Thus, here we reveal the top 5 business intelligence trends in 2021. But, before that learn in brief what BI stands for and its benefits.

What is Business Intelligence (BI)?

Business Intelligence is a business-oriented feature of Data Analytics. Wherein the data collected by the business is changed over into knowledgeable and actionable insight with the goal to turn out to be more profitable. Business Intelligence can have numerous aspects including analyzing various types of data that are generated by the business. Afterward, present the resultant acquired from the data to decision-makers in the business using reports, presentations, graphs, dashboards, summaries, and so on.

In simple words, Business Intelligence doesn’t straightforwardly tells the decision-makers what the roadmap should be followed and what decision to make. Yet it gives details of all the aspects based on the data analysis that can be used to make an intelligent and well-informed decision. 

For instance, suppose a global car business needs to analyze their car sales on a country-by-country basis and understand which models perform better. They can utilize Business Intelligence to gather information about all the models they have. Such as worldwide sales, popular models among customers, some feedback for improvement, and many more. By breaking down such details in numerals form, the business can learn about which models are more famous in each country. In addition to that, how they can make improvements in their products or sales to generate profit.

Overall, Business Intelligence serves multiple purposes and introduces numerous benefits to businesses. Let’s learn about the benefits of using BI systems in your business.

Benefits of using BI Software in Your Business

• Fast and accurate reporting
• Valuable business insights
• Competitive analysis
• Better data quality
• Increased customer satisfaction
• Identifying market trends
• Increased operational efficiency
• Improved, accurate decisions
• Increased revenue
• Lower margins

Top 5 Business Intelligence Trends in 2021

1. Artificial Intelligence

The U.S. companies are taking up their AI interests in a post-COVID world, with the outcome sure to reflect in the coming years. In a survey by PWC, 86% of executives said that AI will be a standard technology at their organization in the next few years.

Regardless of whether through personalization driven by Machine Learning, data augmented prep, auto-outlined data visualizations or clarifications made by natural language generation, AI technology has influenced BI and is here for the long haul. On account of machine learning algorithms and advanced neural networks the modern BI trends empowered with augmented analytics. It can identify irregularities, examine sudden events and dig deeper to find the most useful and relevant data possible. As opposed to its name, Artificial Intelligence accumulates information and makes it more accessible to all.

2. Self-Service Business Intelligence Would Be On Rise

The BI trends and tools have used the data stores in central distribution centers. However, a business has become inescapable and needs admittance to a tremendous amount of data in a short time-period by various users. This results into, decrease in reliability of data stores.

Therefore, the organizations are now moving to self-service business intelligence that gives more independence and flexibility. Self-service Business Intelligence trends provide various classifications of users and their obligations.

They have perceived that 5% of business analysts depend on BI tools of which ¼ users need greater flexibility while going through business data.

3. Natural Language Processing

Natural Language Processing (NLP) is an AI-technique. It shows computer programs how to correctly translate a language into a structured form that can be interpreted by humans. It has contributed a lot to the development of business intelligence.

Business Intelligence trends in NLP have definitely improved; how organizations gather and filter relevant data. Examples of NLP that BI applications will depend on considerably more, in the future include: 

Natural Language Generation: Converting any structure into a human language, for example, the technique used in Cortana. 

Machine Translation and Learning: Machine Translation works by changing one language to another like Google Translate. ML is totally a unique area that deals with how well a PC or software can train itself to manage new issues.

Speech Recognition: This is the technique used by software like Siri, Google Voice, Echo Dot, etc. for understanding a human’s perception when you communicate with them and react in a similar manner.

4. Increase in SaaS and Cloud Adoption

The rapidly increasing number of organizations are trying to migrate to cloud services and leverage all the advantages of cloud-based BI. Regardless of hosting on a private or public cloud or preferring a Software as a Service (SaaS) BI trends. The demand for cloud BI keeps on growing at an enormous speed. Thus, based on a 2020 Cloud Computing and Business Intelligence Market Report, 95% of enterprise software vendors think of it as mandatory to have and 54% of enterprises say it’s either basic or vital to their business drives. 

For organizations and their IT teams, some of the critical advantages of executing cloud BI include:

• Stress reduction due to hands-off updates and maintenance.
• The Cloud data are accessible on any device from any location.
• Increased scalability and flexibility.
• Easier administration and management.
• Higher cost efficiency and lower ownership cost.
• Security given by calamity assistance and data backup.

5. Automation

Automation is a growing and trending system in the market. According to Adobe’s Digital Trend Report 2020- 64% of big organizations said they used AI to automate data analysis in 2020, up from 55% in 2019. Automation can deal with repetitive tasks and tedious obligations in any case performed by humans, freeing up those assets for others.

As data analytics increases and data volumes scale up continually. Then automation will be essential to remove manual data processes, considering additional time spent on decision-making. The capacity to quickly examine data and act on the outcomes defines BI. Hence, the automation speeds up business processes at all steps of the data workflow. This makes it simpler for users to find the solutions for their business questions whatever they need.

Conclusion

As a company, being data-driven is not any supreme service, however it is the expectation of the modern business world. The last decade of 2011-2020 has been a major time-period for data. Thus, 2021 and onwards it is definitely going to be an exciting time of leaving all the past hypes. It boosts to move forward to extract maximum value from the online business intelligence software by following the latest trends of business intelligence. 

Thus, the companies in all the industries should aim to use all the insights effectively with business intelligence systems as the data becomes more diverse and complex. Due to this, the year 2021-22 will witness a huge increase in the demand for Data Analyst or Data Scientist. Especially the ones who can come up with a unique and reliable solution for the data related issues.

So, if you also like to hire a dedicated data analyst or data scientist then EngineerBabu is the right destination for you. We understand business needs and dedicatedly work to deliver best services and quality business solutions. For more information and detail you can Contact Us, we are here to help you in the best possible way we can.

The post Top 5 Business Intelligence Trends in 2021 appeared first on EngineerBabu Blog.

These healthcare software or applications help doctors and patients to manage vital health information. In addition to that, it also ensures to improve the quality of care and services required and make it more cost-effective for both doctors and patients. The healthcare administration tools refer to knowledge-based, decision support IT programs. These healthcare tools offer guidance, assistance, and can also