Data Science at Greenlight: Growing with our Families

Data Science at Greenlight builds machine learning (ML) and advanced analytic solutions to drive our business. As one of the last pieces of the data team to be built, we are still in the early phases of building models and defining our process. As we grow, we strive to have both immediate impact, but also lay the groundwork for the future by being thoughtful about best practices, tools, and processes. We’ll look at data science’s operating model, tools, best practices, and vision for the future as Greenlight grows. While Greenlight and its data science muscles grow, so do the families we serve. As an example of the power of Greenlight’s data, we’ll look at what data tells us about how our families’ behavior changes as they grow. We’ll look at examples of a family’s journey. From what kind of chores kids get at different ages, to how a child ages through the app, we’ll see that our data gives us the power to personalize our product to better serve our families.

Session Time


Bart Masters

Director, Data Science

Greenlight Financial Technology, Inc.


Bart lives in Birmingham, AL with his 4 children and 2 dogs. A native of Hoover, AL, he went to Samford University and then Vanderbilt. After living in Nashville for 5 years, he returned home to Birmingham. Bart started off as a data analyst and statistician, and then focused on data science and ML (machine learning) as an individual contributor, before transitioning into leadership. He has been leading teams in advanced analytics and data science for approximately 7 years in healthcare, biosciences, and technology companies. Currently at Greenlight, he is building and leading a small ML team to have a big impact in an aggressive late-stage startup environment. Previously at Shipt, he led and grew the enterprise ML team and eventually specialized in operational machine learning models that drive pay and efficiency in the gig work environment. When he’s not doing data science or chasing children, he likes to play tennis and go running.

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