Data Science is far beyond the ‘Data Scientist’ and ‘Data Engineers’

Hunting the right career path, especially the right career transition path, has never been so easy, so the data science career switch. While ‘how to become a data scientist? (mostly for data science aspirants who are non-technical).’ or ‘how to become a data engineer? (mostly for aspirants with IT/software background ).’ has become the top searched phrase in google. Unfortunately, about 70% of total aspirants miss the availability of other data science job roles that are too high in demand. 

Yes, ‘data scientist’ and ‘data engineer‘ are not only the data science job roles existing in the field of data science and artificial intelligence (AI). Rather, there are plenty of other technical, entry-level, and expert level jobs with high-pay scales you can target for. So you can say, till now, these are the hidden scopes. Exploring those will help you plan your career transition learning path accordingly.

So, let’s have a look at the top 8 data science job roles in 2021.

  1. Machine learning engineer
  2. Machine Learning Scientist
  3. Data Analyst
  4. Database Administrator
  5. Data Architect
  6. Business Intelligence Developer
  7. Data Statistician
  8. Analytics Translator

1. Machine learning Engineer

Machine learning engineer has been a quite general term for the last two years among all eight roles. This is a sub-branch of (AI) that generates the foundation step of the most advanced AI sun branch, ‘deep learning

While data scientist job roles demand basic to moderate degree of programming, statistical, and algorithmic knowledge, splendid proficiency in several data science tools handling, ML engineers must-have skill set includes in-depth knowledge of algorithms, a strong background in software engineering, and an impressive degree of coding capability. 

With the increasing demands of automation, the market demands for ML engineers are on a brisk hike. At present, 15464 machine learning engineers job vacancies are there in India (Source: LinkedIn).

Lists of Skills required to step into a promising machine learning engineer career:

  • Basic knowledge of statistical modules like probability theories and hypotheses, differential calculus, binomial and polynomial distribution theories, linear algebra, etc. 
  • knowledge of different machine; earning frames works, and algorithms
  • Adequate Infrastructure knowledge, especially the ability to deploy the right ML models as per business requirements. 
  • Ability to optimize machine learning models over different cloud services according to the situational needs of the business.  
  • Proficient in writing clean and maintainable codes and the ability to containerize the same based on contemporary business problems. 
  • Development of customized and highly problem-specific applications for generating better analytical insights and data-driven business decision-making with the least possible human involvement (automation).

2. Machine Learning Scientist

‘Scientist’! Yes, compared to the engineer’s variation of the ML domain, scientist sounds offbeat but sooner ‘machine learning scientist’ will become a very popular job role.

So, what does an ML scientist do? Unlike the other scientist position, the key roles of  Machine learning scientists lie in researching the existing ML frameworks, algorithms, apps, and software for newer inventions on the same. The job role is more like Accademia but needs a strong technical background. The final output of this job role includes publishing research papers, training, and development. In short, you can say, ML scientists are associated with the R&D section of data science.

While this job title seems completely new to you, hitting a search on Linkedin for the same will give a result of 921 vacancies available in India (job number as of May 10, 2021).

Lists of Skills Required to Step into a Promising Machine Learning Scientist Career:

  • Strong knowledge of machine learning algorithms
  • Exceptional proficiency in data manipulation to explore the further scopes of improvements in current data manipulation techniques and tools.
  • Core knowledge of statistical approaches and concepts to develop new machine learning algorithms to better current insights.
  • A good grip in coding knowledge is also required as the position requires testing identified algorithms for experimental purposes. 
  • Extremely high level of critical thinking skills via the technical mind.  

3. Data Analyst

Data analysts are again a relatively known term, but very few know that this is a part of data science and offers lucrative salary packages for promising candidates. Some companies now post job vacancies for data scientists, where the job roles remain limited to the core data analyst domain. 

But what’s the difference between a data analyst and a data scientist?

The analysts’ role is to identify and apply the possible number of insightful report generation from available data sets. A data analyst’s insights should address contemporary business problems in the long run by implementing small advancement or alternation into the current data analysis strategies over time. 

Compared to a data scientist, a data analyst has to work more on data visualization. On the contrary, the role of a data scientist comes with the additional responsibilities of basic programming,  implementation of basic statistical concepts within the data analysis strategies, management of data storage, etc. 

Lists of Skills Required to Step into a Promising Data Analyst Career:

  • Strong knowledge of several data visualization and calculation tools/ programming libraries like Matplotlib, NumPy.
  • Ability to work proficiently with data analyzing software and applications like SPSS and Advanced excel.
  • Working knowledge of database query languages like SQL. 
  • Adequate knowledge of tracking web analytics and performing A/B testing of gathered data sets and identifying insights.   

4. Database Administrator

Data scientists, analysts, ML scientists, and engineers work on a huge number of datasets. But what’s about the administrative management of the databases from where such datasets are taken?

The task of database management in maintaining the datasets’ efficacy, security, data clearing, real-time data monitoring, and new data storing is not that easy, especially when the volume of daily data generation is too high around, 2.5 quintillion. 

Here comes the need for a separate job role, ‘database administrator.’ Such professionals are responsible for managing, maintaining, and monitoring the huge databases that are going to be used by data analysts, data scientists, and other data science professionals. 

At present, 11273 database administration vacancies in India are listed (Source: Linkedin Job).

Lists of Skills Required to Step into a Promising Database Administrator Career:

  • Strong knowledge of database management systems like SQL, MySQL, MongoDB, Oracle database, etc. 
  • Proficients in data cleaning tools and software handling to keep the databases in their most performing states. 
  • Ability to implement and manage data security.
  • Maintaining regular and timely communication across the different organizational departments like IT, marketing, finance, etc., uses the databases you manage.
  • An eye to small details for reviewing and deploying databases and artefacts underuse. 
  • An ability to transform all the complex problems into a simpler approach.

5. Data Architect

Do you resemble this job role with a software architect? Well, you are right, but not 100%. 

While software architects are associated with developing and designing problem-solving software as per business requirements, data architects concentrate on developing and advancing databases. But yes, designation wise you can say, a data architect in data engineering is similar to a software architect in a software engineering career. 

Although this is a comparatively newer role in the data science job market, the number of vacancies is growing very fast. As of today’s update, searching with the ‘data architect’ title provides 5882 job listings in LinkedIn job search for India. 

Lists of Skills Required to Step into a Promising Database Architect Career:

  • High level of efficacy in procedure generation, management, and review to map the entire database development and management problems depending on business scenarios.
  • In-depth knowledge of all of the most demanding database management systems like SQL, MySQL,  Oracle, NoSQL, etc., to provide solutions even in deadlock conditions of database performance. 
  • Extensive working knowledge in several cloud-based data management services like Amazon web services (AWS) cloud (EC2, Lambda, etc.), Oracle Cloud, Google cloud database, MongoDB, IBM db2, etc. 
  • A strong foundation in Linkedin statistics and applied mathematics. 

6. Business Intelligence Developer

AI-powered Business intelligence (BI) tools are in high demand in 2021, so the demand of Business intelligence developers. 

Business intelligence offers tricky solutions to most of the bottleneck conditions to business problems. Only the gridlock conditions and simpler issues BI can lead to unique solutions that ensure the long run of business. 

The key responsibility of the BI developers contains developments of AI-powered BI tools and applications, monitoring and maintenance of the similar existing applications as per identified business requirements. This job role is a part of data engineering.

 According to LinkedIn, around 2634 BI developer jobs are presently available in India.

Lists of Skills Required to Step into a Promising Business Intelligence Developer Career:

  • Adequately strong working knowledge on several DBS. 
  • Expert in data analysis.
  • Proficient in working and core programming concepts of popular BI tools like Hadoop, SAS, Apache, Sisense, etc. 
  • Core knowledge of software development for launching newly evaluated BI interfaces. 
  • High efficacy in debugging and troubleshooting for newly launched BI applications.
  • Sound knowledge of business development processes, including different business models, marketing theories, etc. 

7. Data Statistician

We all know statisticians are the founders of data science. Yet, due to the more advertised impact of computer science on the same, we are on the way to forget the contribution of statisticians in the advancement of data science.  

Statisticians have been in high demand since the ancient decades and still hold the same degree of demand in machine learning and AI. Without the help of statisticians, the generation of unique and powerful business insight would never be possible.

Lists of Skills Required to Step into a Promising Data Statistician Career:

  • Core knowledge of statistics and applied mathematics.
  • Core programming knowledge of python, C++, SAS, Java, R. 
  • Unique ability to circulate and communicate statistical findings with non-statistical personnel of the company, like marketing head, finance head, etc.
  • Exceptional level of problem-solving skills along with advanced analytical and critical thinking abilities. 
  • Great proficiency in working with several data analytics, AI, and BI tools.
  • Strong industry knowledge to come up with sustainable statistical solutions. 

8. Analytics Translator

It is not a straightforward job to frame market issues into actual data science initiatives. It takes some technological skills, but also some understanding of the industry, which is a mix that you won’t find anywhere. A common error of organizations is to treat any issue as an apprenticeship, and it isn’t very good for the team’s morals. Problems that could more efficiently be resolved, such as determining market rules, only waste data science teams’ time and resources. 

Even though a company’s data scientist and data engineers make efficient data-driven insights and data management applications, the concerned departments like marketing, finance, operation management, etc, might fail to implement the best practices of generated insightful business decision-making strategy.

Here the job title ‘analytics translator‘ draws the solution. These professionals work as the bridge between the data science professionals and data engineering experts of the organization. Their key responsibilities include communicating the insights generated by the data scientist and analyst with professionals making the requisite business decisions (for which the insights have been generated) in the frontline. 

Lists of Skills Required to Step into a Promising Analytics Translator Career:

  • Good knowledge of AI and ML technology, including the concept of ML models, algorithms, etc. 
  • Core industrial knowledge along with the knowledge of the respective business process, business models.
  • An adequate degree of statistical understanding.
  • Excellent level of communication skills like convincing ability, easily understandable explanation capability, etc.
  • Updated knowledge on market trends and technology trends related to data scientists and the concerned business or industrial domain. 
  • Sound knowledge of common data science tools like Tableau, Seaborn, NumPy, Hadoop, and several cloud services like MongoDB, Amazon EC2, etc.

Now you know enough about the hidden but most promising roles in data science. So, next comes the first step of planning your data science career transition through one of these roles. 

And what is the first step? Choosing the right guidance. Nothing but a highly credible certification program in Data Science with end-to-end career switching guidance can be the best option here.

But where will you get such a course?

Well, you can join the Fullstack Data Science Courses (for working professionals) and Internship associated data science courses (for fresh graduates) offered by Skillslash. 

They have different courses specially designed for you based on your domain experiences and years of experience. You will be guided starting from course selection to getting a job by cracking the most challenging interviews. For telephonic counselling, submit your resume here
At the end of the Skillslash Data Science Course, you enter into the competitive data science job market with creditable real-time industry project experience and domain-specific skill sets. These are not only the features Skillslash offers you. All of the Data Science and ML courses of Skillslash also offer you lots of unique features that make your career transition more sustainable, and yes, all you get at affordable fees. To know more about those features, visit

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