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7 Fastest-Growing Job Roles In Data Science & How To Work Towards Them

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7 Fastest-Growing Job Roles In Data Science & How To Work Towards Them

Key takeaways

  • Data science has evolved into a strategic component for organisations, driving significant job creation.
  • The demand for data scientists is high, with approximately 97,000 available positions in the field.
  • Analytics professionals in India earn significantly more than average software engineers, with rising salaries noted.
  • New job titles and stringent entry requirements are emerging as the data science industry formalises roles.
  • Entry-level analytics professionals can expect modest salary increases as they gain experience.

Takeaways drafted with AI from the article text.

In an industry that is experiencing a steady rate of job creation, data science itself has moved from just a buzzword to a strategic component in organisations. In addition to this, data scientists are increasingly taking on more strategic roles as organisations employ a product-centric view of data. It is a field that promises tremendous job growth and higher earning potential. Our latest research posits 97,000 jobs are available in this buzzing field.  On the hiring end, there is a significant overall growth in jobs in the field. Our recent Salary Study indicates Data Analytics professionals are currently benefiting from the big data wave with analytics professionals earning 26% higher than an average software engineer in India. In fact, salaries of analytics professionals continue to rise with a pronounced growth in median salaries over a period of 2016-2018. Analytics salaries continue to exceed other software engineering roles with analytics professionals out-earning Java counterparts by almost 50% in India. Freshers joining the field can enjoy a 1.8% increase in salaries of entry-level analytics professionals with experience between 0 to 3 years. 

Job Roles Are Growing In Data Science 

This exponential industry growth has led to a new trend ⁠— job positions are getting more formalized, there are stringent entry requirements and new titles are emerging on the scene. For example, we see openings for Business Analyst and Business Intelligence Analyst that may sound as if they aren’t very far removed but professionals have a different career path and different earning potential also.  The growth in the number of jobs is also accompanied by new job titles. While some of these job roles may have certain overlapping responsibilities, there are also some clear distinctions. Today, Data Science presents plenty of opportunity for non-STEM majors who lack a programming background to enter the field.  Given this rapid pace of development, we dig deep into the fastest growing job roles along with an avenue to enter this exciting field. To get a clear view of the new roles, AIM spoke to  AnalytixLabs to understand how data science, that always existed as statistical analysis has evolved into a sophisticated business function now and given rise to roles which require a blend of skills.   Not only that, we tell you how to work towards the data science job you want and learn critical skills to move up the career ladder. 

7 Fastest-growing Job Roles & How To Work Towards Them

1) Business Analyst / Data Analyst / BI Analyst 

Role: Business Analyst understands the business and data requirements, translates the operational requirements of clients, has deep domain expertise and can also perform data collection and reporting. Core skills required are combining analytical and operational skills to drive projects forward and a deep understanding of how business analysis to deliver more value to organisations.  The key difference between Business Analyst  and Data Analyst is that DAs work with large datasets, have a quantitative background, experience with programming and analytics while BAs work more on the business end, gathering and analysing data, understanding project scope and requirements to make effective decisions. The two roles require different skills.  Meanwhile, a BI Analyst works primarily on the reporting end, builds and deploys reports and dashboards and make recommendations based on the insights.  BI Analyst have excellent dashboarding skills and are proficient in SQL and Tableau. However, if you are a numbers-driven person keen to chart a new career, then there is one course that can help build the core competencies for all the data-intensive roles.  Core Skills: Excel, SQL, Tableau to advanced tools like R, Python Data Science Career Avenue: Since the role of BA/DA relies heavily on reporting, Data Analytics & Visualization training course provides a well-defined career path for both BA and DA role

2) Business Analytics Manager

Role: One of the most popular and in-demand roles, BA Managers are highly sought after to drive analytical solutions, work closely with technical delivery teams to implement these solutions, have domain knowledge and most importantly strong consulting skills.  Interestingly, this in-demand industry skill-set can also help one move up the ladder to the role of Data Scientist.  Core Skills: Experience with R, Python, SQL, Tableau, Excel VBA, SAS  Career Avenue: This is a role that requires advanced competencies and a fundamental understanding of statistical concepts, predictive modelling techniques and Python & SQL. This course  offers the best combination of theory and tools and is led by the industry’s leading instructors. The certification course is geared at a broad range of candidates who want to pivot to the data science field and start their career as a BA Manager. The comprehensive course also prepares candidates for the role of Data Scientist. 

3) Data Scientist

Role: Billed as the hottest job in the post-millennial world, the demand for data scientists is high across the board, from large enterprises to startups and e-commerce majors.  Gradually, the market is moving towards a full-stack Data Scientist, somebody who also can also work on a specific application area, for example, NLP or Computer Vision and build market-leading data-driven products. Given the growing need for talent in the space, more courses are now being launched on data mining, programming, analytics etc.  Core Skills: Experience using machine learning techniques/algorithms in predictive modelling and analysis, analytics techniques such as Regression, Classification, Clustering and Time Series is preferred for Data Scientist roles. Of late, Python has emerged as the most in-demand skill for Data Scientists.   Career Avenue: Though the industry is flooded with MOOCs, what’s required is a comprehensive training programme that offers a well-defined, updated curriculum along with placement opportunities. This course offered in Bangalore & New Delhi provides a rigorous, hands-on training in statistics, predictive modelling, Python in addition to fundamental understanding of machine learning techniques.

4) Data Engineer

Role: Data Engineers have become a core addition to the Data Science teams and are one of the hardest positions to fill. Reports suggest that finding data engineers with the right experience and skill-set is a challenge for organisations. Data Engineers are tasked with building data pipelines and work on taking use cases from pilot to the production stage.  Core Skills: Data Engineers have experience with Hadoop-based technologies such as MapReduce, Hive, MongoDB or Cassandra. They also come with a thorough background in data warehousing and NoSQL technologies. Besides, big data technologies they are also expected to have knowledge of general purpose and high-level programming languages such as Python, R, SQL and Scala.   Career Avenue:  One of the most in-depth courses in the industry, Big Data Hadoop training covers the entire Hadoop ecosystem and provides a fundamental understanding of database technologies like Scala, Hive, Apache Spark and Impala. It also gives an introduction to cloud computing and how to manage Hadoop and Spark ecosystems in the cloud.

5) Machine Learning Engineer 

Role: Machine Learning engineers have become the backbone of consumer facing technology companies, dealing with large volumes of data. ML Engineers are tasked with designing the solution architecture for applications and automate the process of model training, testing and deployment to ensure a continuous delivery pipeline. In a nutshell, ML Engineers ensure machine learning models and pipelines are put into production.  Core Skills: ML Engineers have a thorough understanding of data structures, algorithms and object-oriented programming. They also have a background in classical and modern machine learning techniques such as decision trees, clustering, regression and neural networks as well. Their core competencies include mining structured and unstructured data and feature engineering.  Career Avenue: Machine Learning Engineers need to have technical depth and understanding of classical ML techniques and Deep Learning. This specialization course provides an in-depth understanding of popular Deep Learning frameworks, TensorFlow and Keras and how to build neural networks. Candidates can level-up their skills with relevant case studies on computer vision, text data processing, image processing, speech analytics (Speech to text / Voice tonality) and IOT.

6) Big Data Specialist

Role: Big Data Specialists are at the forefront of solving the most complex data challenges, especially in consumer facing companies which experience high volumes of data. Companies require Big Data Specialists who has experience with database and analytics technologies, can work in an enterprise environment and can lead global data warehousing and analytics projects. This role also goes by the title of Big Data Developer or Database Engineer.  Core Skills: Experience with big data technologies Hadoop, Spark, Pig and Hive in addition to knowledge of OLAP and reporting. Understanding of statistics and machine learning is a  value-add. Experience with Statistics and Machine Learning.  Career Avenue: So how does one build hands-on experience as a big data specialist or big data developer. This advanced certification from AnalytixLabs provides the competencies in database technologies and advanced analytics concepts and gives candidates access to virtual labs to get hands-on training. You can learn some of the most in-demand database ecosystem tools  like Hadoop, Apache Spark, Hive, Spark Streaming and Python for data analysis.

7) MIS Consultant/ Data Visualization Consultant

Role: MIS Consultants are tasked with designing and managing a platform for collection of data, reporting and dashboarding skills. Data Visualization experts gather data,  analyze data and work on reporting and dashboarding. They are tasked with leading and designing reports and dashboards and have extensive experience with a range of BI tools and SQL.  Core Skills: Data Mining, reporting, writing SQL queries and dashboarding and collaborating with team members are some of the core skills required.  Career Avenue: This advanced training certification goes beyond Excel and provides job-oriented Analytics & Reporting skills with MS-Excel, VBA, MS-Access, SQL and Tableau. In addition to this, there is a strong focus on dashboarding skills, VBA macros which are strengthened with insightful case studies.

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Corrections: AIM corrects errors of fact and notes the change on the story. Spotted one? Tell the editors. Read our editorial standards.

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