Sep 23–26, 2019
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Executive Briefing: Creating a center for data science from scratch—Lessons from nonprofit research

Gayle Bieler (RTI International)
11:20am12:00pm Thursday, September 26, 2019
Location: 1E 10/11
Secondary topics:  Culture and Organization
Average rating: ****.
(4.50, 4 ratings)



Gayle Bieler explains how she built a thriving center for data science within a large, well-respected nonprofit research institute and shares some of its most impactful projects and best adventures to date, that have solved important national problems, improved local communities, and transformed research.

The mission of the center at RTI International—a team of 24 data scientists, statisticians, software developers, and visual designers—is to improve the human condition: “data science for social good.” You’ll learn what it’s like building and leading such an organization from scratch after 26 years as a statistician at RTI. Gayle also outlines several important considerations: choosing a leader, team composition, continuous recruitment and retention efforts, the necessity of technical as well as domain and soft skills, team versus group culture, and elements of the center’s philosophy—namely rapid prototyping, human-centered design, and an open source mindset—that drive success in collaborating with domain researchers across the company, fostering staff engagement, and creating a continuous learning environment in a fast-moving field.

What you'll learn

  • Learn how RTI International is harnessing the methods, mindset, and energy of data science to solve important social problems and make government work better for all of us
Photo of Gayle Bieler

Gayle Bieler

RTI International

Gayle Bieler is director of the Center for Data Science at RTI International, where her team of 24 data scientists, statisticians, software developers, and artists is busy solving important national problems, improving local communities, and transforming research. A a statistician by training, with 31 years’ experience at RTI, she’s also experienced in statistical analysis of complex data from designed experiments, observational studies, and software development for sample surveys. She’s passionate about building and leading a vibrant data science team that solves complex problems across multiple research domains, that is a hub of innovation and collaboration, and a place where people can thrive and be at their natural best while doing meaningful work to improve the world. The most important things to her are people and impact, in that order. She holds a master’s and a bachelor’s degree in mathematics from Boston University.

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