Executive Briefing: The care and feeding of data scientists
Who is this presentation for?Data scientists or analysts
As a discipline, data science is relatively young, and the job of managing data scientists is younger still. Many people undertake this management position without the tools, mentorship, or role models they need to do it well. You’ll gain insights from a recent Strata report that examines the steps necessary to build, manage, sustain, and retain a growing data science team and how data science management is similar to but distinct from other management types.
Katie Malone and Michelangelo D’Agostino share concrete tips for balancing and structuring a data science team, recruiting and interviewing the best candidates, and keeping them productive and happy once they’re in place.
- Experience managing a team of data scientists
What you'll learn
- Explore data scientist archetypes, such as operations and research, that fit an organization
- Gain thought starters for recruiting, interviewing, and hiring members for your data science team and ideas for retention
- Explore Agile and objectives and key results (OKR) methodology to determine how the team could work together and explore a career ladder through guidance and mentorship
Katie Malone is director of data science at data science software and services company Civis Analytics, where she leads a team of diverse data scientists who serve as technical and methodological advisors to the Civis consulting team and write the core machine learning and data science software that underpins the Civis Data Science Platform. Previously, she worked at CERN on Higgs boson searches and was the instructor of Udacity’s Introduction to Machine Learning course. Katie hosts Linear Digressions, a weekly podcast on data science and machine learning. She holds a PhD in physics from Stanford.
Michelangelo D’Agostino is the senior director of data science at ShopRunner, where he leads a team that develops statistical models and writes software that leverages their unique cross-retailer ecommerce dataset. Previously, Michelangelo led the data science R&D team at Civis Analytics, a Chicago-based data science software and consulting company that spun out of the 2012 Obama reelection campaign, and was a senior analyst in digital analytics with the 2012 Obama reelection campaign, where he helped to optimize the campaign’s email fundraising juggernaut and analyzed social media data. Michelangelo has been a mentor with the Data Science for Social Good Fellowship. He holds a PhD in particle astrophysics from UC Berkeley and got his start in analytics sifting through neutrino data from the IceCube experiment. Accordingly, he spent two glorious months at the South Pole, where he slept in a tent salvaged from the Korean War and enjoyed the twice-weekly shower rationing. He’s also written about science and technology for the Economist.
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