• Own and extend our offline eval suite across products — datasets (capability + regression), judges, metrics • Build and maintain online quality dashboards: resolution rate, CSAT, thumbs up/down, LLM-as-judge signals, error rate, latency • Close the production feedback loop: mine failure patterns from real traffic → turn them into regression cases → propose fixes to Product and domain experts • Harden methodology: judge stability, non-determinism handling • Translate numbers into decisions – weekly syncs, clear trade-offs, no dashboards for their own sake

• Own and extend our offline eval suite across products — datasets (capability + regression), judges, metrics • Build and maintain online quality dashboards: resolution rate, CSAT, thumbs up/down, LLM-as-judge signals, error rate, latency • Close the production feedback loop: mine failure patterns from real traffic → turn them into regression cases → propose fixes to Product and domain experts • Harden methodology: judge stability, non-determinism handling • Translate numbers into decisions – weekly syncs, clear trade-offs, no dashboards for their own sake

Title: Lead Data Scientist Location: San Francisco (Hybrid) Department: Data Job Description: 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 Role Overview: 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 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 that 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. What you’ll be doing: - Build, test and roll out new underwriting and risk models to better predict risk - You’ll have ownership of the full modeling lifecycle from conception through to production and realize every bit of impact along the way. - Build, test and roll out new or improved models related to fraud and payments. - Contribute to building best practices for feature development, model training and model testing and monitoring. - Analyze how our customer base is shifting as we grow and pinpoint areas we can improve. - Help our existing engineering and business teams achieve our cross-functional goals. - Mentor more junior data scientists or aspiring data scientists across the data team. What you have: - 6+ 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 Who You Are - 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 $185,000 - $215,000 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. Our Benefits & Team - Medical, dental, and vision insurance - Flexible PTO Policy - 401k plan - Paid Parental Leave - Physical and mental wellbeing benefits including Wellhub for access to virtual workouts and discounted gym memberships, and Headspace for covered virtual therapy sessions and unlimited on demand health support - Monthly reimbursements to use against wifi and cell phone bills - Annual reimbursement for Learning & Development - Help hard working Americans build a brighter financial future - High-growth company - A dynamic, flexible and collaborative start-up work environment with a highly talented team Brigit is committed to providing equal employment opportunities for all applicants and employees without regard to race, religion, color, sex, pregnancy (including breast feeding and related medical conditions), national origin, citizenship status, uniform service member status, age, genetic information, disability, or any other protected status in accordance with all applicable federal, state and local laws. We are proud to be an equal opportunity workplace. If you require reasonable accommodation in completing an application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please email accommodations@hellobrigit.com. Disclosures: - For information on our data privacy policies, see the Brigit California Personnel Privacy Policy. - Brigit uses E-Verify for employment authorization. See the E-Verify and Department of Justice websites for more details.

• Own and oversee cross-workstream alignment, dependencies, and critical path across the full programme lifecycle. • Define, own, and continuously evolve programme-level artefacts, governance, and reporting to support decision-making and assurance. • Provide clear, insight-led executive reporting to senior client and Valtech leadership, highlighting risks, opportunities, and recommendations. • Own programme assurance, including regular health assessments and proactive intervention. • Shape and mobilise new initiatives and opportunities within the engagement. • Identify and drive improvements to delivery models, team structures, and ways of working. • Act as an escalation point for complex delivery, commercial, or stakeholder challenges. • Ensure delivery outcomes align with strategic client goals and long-term account objectives.