Senior 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 2026 Best Midsize Companies to Work For in New York City

• 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

At Brigit, we’re focused on giving the 100M Americans who live paycheck to paycheck access to more affordable financial services and getting them on the path to better financial wellness. As a Data Scientist on our team, you’ll be responsible for building, improving, and maintaining the key ML models that enable our services. The key problem spaces we are focused on are:

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

• Identify fraud early, so we can focus on customers who rely on us for support

• Optimizing our transaction timing so we aren’t causing our customers to overdraw their accounts.

We have access to rich, structured data that we can use to derive insights and build complex models. In addition to supporting new use cases when needed, you will also have the opportunity to help us stand up best practices and collaborate across Data Science. Analytics, Product, and Engineering teams.

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  Build, test, improve and roll out new models in a variety of problem spaces.

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

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  Help our existing engineering and business teams achieve our cross-functional goals.
  

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

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

• Proven expertise 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

• Experience creating training data sets, training models, tuning hyperparameters, performing validation, running A/B tests in production, creating and owning performance 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)

• Experience building end-to-end data science solutions to address business needs: from ideation to deployment & AB testing

• Strong written and verbal communication skills, with the ability to explain complex concepts to various audiences

• Passionate self-starter who is always looking for ways to optimize, test, and improve

• Ability to operate through ambiguity by asking questions and learning quickly

• Always willing to collaborate and help your colleagues to do their best work.

• Passionate about making a difference in people's lives through your work

The anticipated annual base salary for this position is $175,000 - $200,000 with a 10% annual bonus opportunity. This range does not include any other compensation components or other benefits for which an individual may be eligible. The actual base salary offered depends on a variety of factors, which may include as applicable, the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job.