Data Scientist - Credit

Best Egg is a market-leading, tech-enabled financial platform helping people build financial confidence through a variety of installment lending solutions and financial health tools. We aim to help customers make smart financial decisions and stay on track, so they can be money confident no matter what life throws at them. We offer top-tier benefits and growth opportunities in a culture built on our core values: Put People First – We foster an inclusive, flexible, and fun workplace. Create Clarity – Open communication drives trust and results. Get Things Done – We focus, prioritize, and deliver with excellence. Deliver with Heart – We lead with kindness, humility, and strong teamwork. Listen to Our Customers – Their needs drive our innovation.   Barclays has entered into an agreement to acquire Best Egg with closing expected to take place in Q2 2026. This acquisition will give us the resources and capital to continue on our mission and drive our strategy forward. With an aligned culture, lower cost of funds, and increased employee growth opportunities across a global brand, we are excited about the future of the Best Egg brand under the Barclays umbrella. We are looking for collaborative, innovative team players who like to solve problems. There will also be immense opportunities for those willing to dive in. If you're inspired by growth and want to make a real difference, Best Egg is the place for you.  We’re proud to be an equal opportunity employer committed to building a diverse, inclusive team. We are seeking a Data Scientist to drive critical risk decisions through design and development of machine learning solutions. This role includes building and supporting end-to-end data pipelines used for modeling and reporting. You will work closely with cross-functional partners, including product, analytics, and engineering teams, to ensure models and insights are built on high-quality, reliable, and well-governed data. This role is great for a data scientist who is passionate about modeling, analytics, and problem-solving — and who wants to see their work directly drive critical business decisions. Duties & Responsibilities

Build high performance ML models that improve credit predictability and customer outcomes.

Build end-to-end machine learning pipelines including data extraction, feature engineering, model building, performance evaluation, and implementation.

Build end-to-end model monitoring pipelines to monitor model performance, including model stability, drift detection, and performance diagnostics.

Develop and own reporting pipelines that support recurring risk reporting, monitoring, and ad-hoc analysis

Explore rich data assets to uncover trends, identify key risk drivers, and generate insights.

Define and monitor data quality metrics (completeness, accuracy, timeliness, consistency)

Manage full modeling lifecycle: model design, data preparation and exploration, feature engineering, model development, evaluation, deployment, monitoring and documentation.

Design experiments and challenger models to test new ideas and drive innovation.

Contribute to audit-ready documentation and support model validation and governance processes.

Leverage modern AI technology and tools to improve workflow, enhance modeling performance, establish and promote best practices.

Work cross-functionally to ensure models are explainable, transparent, and aligned with business goals and regulatory expectations.

Translate analytical findings into recommendations for Strategy, Pricing, and other business decisions.

Build pipelines that are scalable, automated, and well-documented.

Requirement

A Master’s or PhD degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Data Science, Engineering, etc.).

1+ years of experience developing predictive models or performing advanced analytics.

Strong understanding of statistical modeling and machine learning fundamentals.

Proficiency in Python (e.g., pandas, numpy, scikit-learn) and SQL.

Experience working with large datasets.

Experience building end to end pipeline.

Ability to clearly communicate analytical findings to both technical and non-technical audiences.

Experience implementing data quality checks and monitoring.

Demonstrated ownership, curiosity, and ability to deliver high-quality results.

Nice to Have

Experience in credit risk, lending and financial services.

Exposure to cloud environments and modern data tooling.

Familiarity with model monitoring, validation, and model governance concepts.

Interest in using AI tools (e.g., ChatGPT, Claude, Gemini) to accelerate modeling and analysis.