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What makes a great data science team?

Jul 12 2016

Here at Twitch, we’ve been working hard to make evidence-driven decision-making a central part of how we build great products. Data scientists play a critical role in that process. They manage experimentation, contribute to product strategy, design data products, and do deep exploratory data analyses. As the leader of that team, it’s my responsibility to try to create a place where data scientists can be successful and satisfied with the impact of their work at Twitch.

I shared what I’ve learned so far in a talk at Mixpanel’s Office Hours series in May. I present a collection of ten questions that I think you should ask of a team you’re thinking about joining (if you’re looking for a job) or of your own team if you’re looking for ways to diagnose potential problems.

  1. Do you spend the vast majority of your time on projects that take longer than a day?

  2. Do people in the organization have ways to access basic data without asking a data scientist?

  3. Do you spend more time doing analysis than waiting for data?

  4. Is there documentation for major schemas?

  5. Do you have a process for detecting and fixing bugs in data collection?

  6. Is past research work documented and available in a central location?

  7. Does the team have a regular process for reviewing work before sharing it?

  8. Do you run randomized and controlled experiments?

  9. Can you report negative results without major political pressure?

  10. Can the CEO (or other leader) name at least one way the team contributed that quarter?

You can learn more about data science work at Twitch at our team homepage. If you’d like to read more about these questions, check out a longer version of the list. We are hiring data scientists and data science managers, so if you’re interested in working with us, we’d love to hear from you! We’re also hiring user experience researchers, a head analyst, and an analytics product manager.

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