What Does a Data Scientist Do?
A Data Scientist is a data expert that extrapolates insights from large data sets to help organizations solve complex problems. To do so, Data Scientists combine computer science, mathematics, statistics, and modeling with a strong understanding of their business and industry to unlock new opportunities and strategies.
What Are the Responsibilities of a Data Scientist?
A Data Scientist’s specific tasks vary greatly depending on the industry they’re in and the company they work for. Generally speaking, though, a Data Scientist can expect to encounter some or all of the following tasks and responsibilities.
- Researching an industry and company to identify pain points, opportunities for growth, and areas for improvement in efficiency and productivity (among other things).
- Defining which data sets are relevant and useful, then collecting or extracting that data from various sources.
- Cleaning data to remove anything unusable, and testing it to confirm that what remains is accurate and uniform.
- Creating and applying algorithms used to implement automation tools.
- Modeling and analyzing data to identify latent patterns and trends.
- Visualizing data or organizing it into dashboards that other members of the organization can consult.
- Presenting findings and making recommendations to other members of the organization.
How Do Data Professionals Spend Their Time?
To find out how data professionals spend their time, BrainStation’s Digital Skills Survey examined five main jobs in the field: Data Analyst, Researcher, Business Analyst, Data and Analytics Manager, and Data Scientist. What it found was that, across all these job titles, “data wrangling and cleanup” takes up the bulk of one’s time.
In the same survey, respondents working in data science said the ultimate objective of their work is most often the optimization of an existing platform, product or system (45 percent), or the development of new ones (42 percent). Unpacking their responses, we found that the work of “optimizing existing solutions” tends to fall to Business Analysts and Data Analysts, while the higher-order work of “developing new solutions” more often falls to Researchers and Data Scientists. What this suggests is that Data Scientists, who typically have more experience and more specialized expertise, are more likely to be involved in decision-making at a leadership level.
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