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Building Effective Data Science Teams
May 13, 2021
At RStudio, we believe successful data science teams require the right technology: open source, code-first data science frameworks based on R and Python, centralized on-prem or in the cloud for ease of collaboration, sharing and administration. However, technology on its own is not enough. It is just as critical to focus on the people in your team. To have a sustainable impact on decision making in your organization, you need to build a productive, effective, and collaborative data science team.
In this panel webinar, you will hear from leaders at Warner Music Group, T-Mobile, Saturn Cloud, The Looma Project, and Caliber Home Loans, about what it takes to build a successful data science team:
Kobi leads Warner Music Group’s global efforts to make “data-backed business decisions” to maximize success for its artists and songwriters.
Greg is an innovative and dedicated analytics leader with 20 years of advanced data analysis experience, heading up a quickly expanding data science team of R and Python users at Caliber Home Loans. Greg has over 30 peer reviewed publications spanning the Economics, Statistics, and Medical domains.
Elaine works at the intersection of data science and business, leading the company to take full advantage of data as part of their analytics-driven, film-based storytelling platform. This includes data strategy, data infrastructure, reporting, and delivery of predictive analytics.
Jacqueline has spent over a decade aiding companies and leading teams at places from DSW and Union Bank to Microsoft and Airbnb and is now building a growing team of data scientists at Saturn Cloud. She also recently co-authored the book “Build A Career in Data Science.”
Nasir is a thought-leader who has built, trained, and retained exceptional data & analytics teams for increasingly better customer experience, with a recent focus on the uniting of two teams given the T-Mobile and Sprint merger. He is passionate about delivering self-service analytics solutions that empowers business users in making quality decisions.
Julia Silge is a data scientist and software engineer at RStudio PBC where she works on open source modeling tools. She is an author, an international keynote speaker, and a real-world practitioner focusing on data analysis and machine learning practice. Julia loves text analysis, making beautiful charts, and communicating about technical topics with diverse audiences.