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Navigating Data Science Jobs in 2024: Roles, Teams, and Skills | by TDS Editors | Feb, 2024

Whether you’re applying to your first internship to running a multidisciplinary team of analysts and engineers, data science careers come with their own specific set of challenges. Some of these might be more exciting than others, and others can be downright tedious—that’s true in any job, of course—but we believe in framing all of these potential drawbacks as opportunities to deepen your knowledge, expand your skill set, and consider new viewpoints.

Our lineup this week brings together a wide range of perspectives and experiences centered around common obstacles in data careers—and proposes effective approaches to overcoming them. Regardless of where you find yourself in your own data science journey, we hope you explore our recommended reads and find insights to bring into your own work.

  • The Data ROI Pyramid: A Method for Measuring & Maximizing Your Data Team
    While Barr Moses’s actionable roadmap is geared towards data leads and executives, it’s an essential resource for data professionals up and down the corporate hierarchy. After all, everyone can benefit from understanding how their work contributes to the business, and how to demonstrate their impact to a broader, non-technical audience.
  • Rebuilding the Portfolio that Got Me a Data Scientist Job
    A year ago, Matt Chapman wrote the definitive hands-on guide to building a data science portfolio (and went very viral in the process). In his latest post, Matt revisits his approach and proposes several key updates for an even more streamlined workflow and a more customizable end product.
Photo by Anastase Maragos on Unsplash
  • 5 Habits Spotify Senior Data Scientists Use to Boost Their Productivity
    After all the effort that goes into landing a good data job, the real work begins: what can you do to excel at your new position without running the risk of burnout and/or impostor syndrome? Khouloud El Alami presents five concrete ideas you can adapt for your needs, and doesn’t skimp on the nitty-gritty details, either.
  • 7 Lessons from an ML Internship at Intel
    After a long stint as a data scientist in the banking sector, Conor O’Sullivan’s most recent career twist took him to a machine learning internship at tech giant Intel; don’t miss his writeup of his experiences there and the lessons he learned while exploring a new industry and organizational culture.

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