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Data Scientist



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Data Scientist


Low: An Associate Degree with/or Professional DASCA “Data Science” Certifications and credentials issued by the Data Science Council of America (DASCA); e.g. Big Data Engineer, Big Data Analyst, Data Scientist, etc., besides Deep Learning/ Machine Learning (DL/ ML) or Data Warehousing and Business Intelligence (DW/ BI) certification;

On the Job Training (OJT), Apprenticeships, IT Workforce Job Training or Experience.

Medium: Bachelor’s Degree in Information Technology or Computer Science or Software Engineering with majors in Math, Statistics and Probability, Physics, DL/ ML, DW/ BI, or a related field; Data Science certifications will be a big plus.

High: Post Graduation in Science, Technology, Engineering or Mathematics (STEM) or a Master’s Degree in Data Science with majors in Math, Statistics and Probability, Physics, DL/ ML, DW/ BI, or related field. Data Science certifications or an MBA, especially in Finance or Marketing will be an added advantage.


Entry-level (0-12 months) $ 85,421
Early career (1-4 years) $ 94,787
Mid-career (5-9 years) $ 108,887
Experienced (10+ years) $ 127,730


Data Scientists are a highly expanding career pathway, in which employment is projected to grow at a blistering 15 percent from 2019 to 2029.


Data Scientists being quintessential “slice and dice” data wranglers need solid statistical thinking with a flair for converting data into human interpretable information. In-depth industry vertical knowledge, curiosity, creativity, strong “hands-on” critical, logical, statistical, and analytical thinking; planning, technical acumen with an aptitude for research, tracking the emerging Data Science related technologies, a spirit of inquiry and scientific temperament along with a strong passion and deep knowledge of Data Science, Architecture, Statistical Data Modeling, and Algorithm techniques, a focused and balanced approach are key to the success. Business knowledge and process orientation will be an added advantage.


Data scientists deal with, gather user requirements, analyze, crunch, and wrangle large voluminous and highly scalable data sets called “Big Data”; consisting of both structured and unstructured data, and that too from varied sources to aid data-driven decision making and insightful reporting. Data science is a confluence of computer science, statistics, and mathematics. Data scientists, using both structured and unstructured data sources to design statistical data models for unraveling and identifying data patterns; and based on this predict future patterns of behavior and thus help in management decision-making. Applications can include merging scientific or commercial data from in-house and cloud databases which are then analyzed and statistically modeled; and using predictive algorithms can project and predict, for example, the consumer’s purchasing behavior, fast-moving inventory, influencing elements, etc.; especially using and analyzing unstructured data from social media, email messages, etc. or emanating from smart devices; to finally decipher and interpret it for well-informed data-driven decision-making, business or scientific solutions. They typically work with corporates, and their work may also involve training, mentoring, and managing subordinates.

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