Data Scientist – Credit

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October 14

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Best Egg

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Finance • Fintech • B2C

Best Egg is a lending company that offers a range of financial products and services, including personal loans, debt consolidation, credit card refinancing, and secured loans using vehicle equity or homeowner discounts. The company emphasizes hassle-free and fast financial service, with an online platform that allows users to manage their accounts, view offers, and access various financial health resources. Best Egg aims to support customers in building a brighter financial future by offering competitive rates and personalized loan terms. Best Egg loans are facilitated through partnerships with banks and are available in various amounts, with flexible terms and conditions.

501 - 1000 employees

Founded 2014

💸 Finance

💳 Fintech

👥 B2C

📋 Description

• Build and enhance credit risk models (e.g., Gen5B Shadow/Gen6, and Autonomous Underwriting) to improve credit predictability and manage portfolio risk. • Work with MLOps, Feature Platform, Credit Strategy, and Implementation teams to build adaptive modeling pipelines that connect model insights directly to automated, production-ready decision flows. • Keep our modeling framework responsive to changes in credit quality and macroeconomic trends. • Conduct exploratory data analysis and experiment tracking to identify key risk drivers and optimize model performance. • Own Python project structure, CI/CD setup, and end-to-end testing for reliable model delivery. • Partner with MLOps and Feature Platform to maintain model pipelines (Metaflow, SageMaker, etc.) and streamline model deployment. • Support model deployment and validation to make sure that models run reliably in production and deliver consistent results. • Improve overall development efficiency through standardization, automation, version control, and reproducibility. • Expand monitoring frameworks to underwriting models. • Support bank and compliance reviews of model performance, PSI/CSI analysis, reject inference, and validation. • Maintain audit-ready documentation and data transparency for internal and external partner reviews. • These efforts complement the broader model monitoring and compliance initiatives led by the Credit DS team.

🎯 Requirements

• Bachelor’s degree in Statistics, Mathematics, Operational Research, Computer Science/Engineering, Data Science or other quantitative major. Master's or PhD is preferred. Other quantitative fields with experience in building Cloud Services/Architect solutions, and data/CI/CD pipelines for AI/ML solutions will be considered. • Solid understanding of the model lifecycle (EDA, modeling, evaluation, deployment) • Intermediate Python and SQL • Data wrangling using pandas (bonus: pyarrow, polars) • Basic version control (git/GitHub) • Experience with Metaflow or similar orchestration frameworks (Flyte, ZenML, SageMaker Pipelines) • Familiarity with cloud environments (AWS preferred) • Model deployment experience (FastAPI + Docker) • Unit testing (pytest) and modern Python project tools (uv, poetry) • Background in credit risk modeling or lending-related ML solutions (e.g., underwriting, early delinquency, loss prediction, fraud detection, etc.)

🏖️ Benefits

• This position is also eligible for an annual incentive bonus based on individual and company performance. • Yearly incentive bonus target 20% of base salary.