Lead Data Scientist

Hi, we're Brigit! A holistic financial health company helping everyday Americans build a brighter financial future. With a business model that is aligned with our customers, we create transparent, fair, and simple financial products that put money back in the hands of our members, help them spend wisely, avoid unfair fees and build their credit quickly. If autonomy, ownership, and having meaningful input at the company you work for is important to you, come join our growing team!

Brigit is doing innovative and exciting work, but don’t just take our word for it, our work is being recognized by others:

• Built In's 2025 Best Places to Work For In New York City

• Built In’s 2024 & 2025 Best Startups to Work For In the U.S.

• Built In’s 2023 - 2025 Best Startups to Work For In New York City

• Fast Company’s Most Innovative Companies of 2022

• Business Insider’s Most Promising Consumer Startups 2022

• Forbes Fintech 50 2022

Role Overview:

As a Data Scientist on our team you’ll be responsible for building/improving/maintaining the most important models which focus on this:

• Identifying credit risk for our customers so that we can help more people in need when they need it 

• Optimizing our marketing spend by predicting LTV for our customers

• Helping us reduce our overall churn by predicting customer churn and improving retention

We have access to rich, structured data that we can use to derive insights and build complex models. In addition to supporting broad analytics use cases when needed, you will work closely with our Product and Engineering teams.

What you’ll be doing:

• Build, test and roll out new underwriting and risk models to understand the risk of our customer base and improve access for our prospective customers by allowing us to take more calculated risks.

• You’ll have ownership of the full modeling lifecycle and get to carry your changes all the way through to our decision process, getting to realize every bit of impact along the way.

• Build, test and roll out other customer related models (such as Churn propensity and LTV prediction) which help us analyze and optimize our marketing and retention efforts.

• Monitor the performance of the models in production and take appropriate actions when necessary

• Analyze how our customer base is shifting as we grow and pinpoint areas we can improve.

• Help our existing engineering and business teams track their goals, supporting the BI function from time to time to time with ad-hoc data analytics 

What you have:

• Advanced degree in data science, statistics, computer science, or related field.

• 5+ years of experience doing data science (modeling + analysis) 

• Proficiency in Python and in-depth understanding of SQL 

• Competent in machine learning principles and techniques

• Experience in python, using industry standard modeling toolkits like sklearn, jupyterlab, pandas, matplotlib, statsmodels, etc.

• Experience in writing complex SQL queries and the ability to put together multiple data sources together 

• Ability to get the train data, train the model, do hyper parameter tuning, perform validation, run the A/B test, do performance monitoring and model monitoring

• Experience building classification and prediction models, testing them in a startup environment and iterating to improve their models.

• Ability to work effectively and communicate ideas/code clearly in a cross functional team environment (Engineering, Product and Business teams)

• ML model deployment in production experience is a plus

• Technical presentatio