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Beyond Math and Python: The Other Key Data Science Skills You Should Develop | by TDS Editors | Nov, 2024


Feeling inspired to write your first TDS post? We’re always open to contributions from new authors.

The roadmap to success in data science offers many different paths, but most of them include a strong focus on math and programming skills (case in point: this excellent guide for aspiring data professionals that Saankhya Mondal published earlier this week). Once you’ve got your bases covered in those areas, however, what’s next? What topics do data scientists need to build expertise in to differentiate themselves from the pack in a crowded job market?

Our weekly highlights zoom in on some of the areas you may want to explore in the coming weeks and months, and provide actionable advice from authors who are deeply embedded in a wide cross-section of industry and academic roles. From mastering the ins and outs of data infrastructure to expanding one’s storytelling skills, let’s take a close look at some of those peripheral—but still crucial—areas of potential growth.

  • Beyond Skills: Unlocking the Full Potential of Data Scientists
    “Data scientists possess a unique perspective that allows them to come up with innovative business ideas of their own — ideas that are novel, strategic, or differentiating and are unlikely to come from anyone but a data scientist.” Eric Colson expands on a thought-provoking premise, namely that companies are under-utilizing data scientists by focusing too much on their technical skills, at the expense of their creativity and outside-the-box thinking.
  • Three Crucial Data Lessons That I Learned from a Data Conference That’s Not Related to AI
    AI has so thoroughly dominated conversations in recent years that it feels refreshing to hear about other ways for data scientists to stay on the cutting edge of their field. Nithhyaa Ramamoorthy reflects on her recent experience at a conference and how it inspired her to pay more attention to issues that might appear less shiny than the latest LLM, but can increase your value as a data practitioner—from cost containment and data translation to information design.
  • The Ultimate Productivity System for Data Science Leaders
    For anyone on the data science management path—whether in its early stages or deeper into your career—it can sometimes feel like leadership skills are expected to grow organically with nothing more than the passage of time. While that might be true in some ways, Rebecca Vickery’s latest contribution spells out some of the concrete steps you can take to ensure you stay focused and productive even as the demands of your role grow.
Photo by In The Making Studio on Unsplash



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