Data Scientist Job Responsibilities

By: Tonya Mead, PhD, MBA, M.Ed, Corporate Trainer and Behavioral Scientist

Data Scientist jobs represent one of the 100 top jobs according to 2022 US News and World Report. Jobs involving data include the multidisciplinary areas of statistics, math, computer science, information technology and business management. If you have an interest in any one or all of these fields, working as a data scientist might be your ultimate dream job.

Data scientist job responsibilities pull from a range of skills that require basic familiarity to mastery of a range of applications. Skilled data scientists have the knowledge, skills and abilities to gain insight from big data, complex algorithms using management theories and scientific methods.

The company, SAS Insights defines a data scientist as one who has the “technical skills to solve complex problems – and the curiosity to explore what problems need to be solved.” The company adds, “they’re part mathematician, part computer scientist and part trend-spotter.” Maybe you are doubtful or are a critical thinker who believes these are exaggerated statements and nonsensical hyperbole.

To assuage your fears and doubts, Harvard University published an article back in October 2012, suggesting that the data scientist is the ‘sexist job of the 21st century.” A few of the data scientist job responsibilities as foreseen by Harvard University still stands true today.

Data Scientist Job Responsibilities

Data scientists have the knowledge, skills, and abilities to:

  • Identify and curate big data sources rich in information
  • Bring structure to unstructured data
  • Collect, store, maintain and clean data
  • Bring structure to unstructured data
  • Analyze data
  • Identify patterns, anomalies and outliers
  • Test findings
  • Introduce new features to products, add new product lines, revenue streams, improve quality, and reduce costs as a result of data analyzed
  • Advise business, nonprofit and government executives on its implications
  • Build compelling stories around data (products, processes, and decisions)
  • Create narratives
  • Communicate these stories, narratives to an audience with a “Call to Action”
  • Conduct academic research
  • Answer complex questions related to the meaning of the data
  • Devise creative approaches for solving problems identified by the data
  • Build and create new tools, algorithms, mathematical and statistical formulas