What is Data Science and who is a data scientist? If you are looking to advance your career in data and analytics or if you want to embark on a data science career, you might be asking yourself these questions. You may even have a few good answers in your mind as well. Below I’ll give you my definitions based on my experience as a Senior Data Scientist as well as an overview of data science’s impact on industry.

Data science is where statistics, data analyses, machine learning and big data tools, and ecosystems meet to understand and analyze a real-world phenomenon.

Turing award winner Jim Gray imagined data science as a “fourth paradigm” of science (empirical, theoretical, computational and now data-driven) and asserted that “everything about science is changing because of the impact of information technology” and the data deluge[1,2].

A data scientist typically has knowledge about statistics, machine learning and big data analysis techniques and tools to infer insights from data.

Data Scientist has been chosen as the best job in the USA from 2016 - 2018 with a median base salary of $110,000

Glassdoor [3]

With the emergence of massive amounts of data and big data tools, there is a need to derive insights from petabytes of data to train machine learning algorithms which can learn and extract the underlying patterns from data. A data scientist helps companies make better business decisions by using available tool kits to transform data and derive insights.

Data science and machine learning are having profound impacts on industry and are rapidly becoming critical for differentiation and even survival.

With data scientists’ ability to frame complex business problems as machine learning or operations research problems, data scientists hold the key to unveiling better solutions to old problems. Data scientists can also make “big data expeditions” for cases where there is no clear objective other than to explore the data for previously undiscovered value[4].

person assessing data

Traditional industry approaches to data analysis use small amounts of data and they often miss out on key insights. A data scientist can improve on these processes and products (e.g. market segmentation) by doing a deeper dive into the data to uncover missing insights.

Today, industries are inevitably coupled with big data and data science has found its way into many industries. For example: financial institutions, health care organizations, retailers and many other industries have become dependent on data science insights in order to survive and progress. Your career in data science can take you to any one of these industries. As more and more industries jump on the big data band wagon, your career options become endless.


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