Senior Data Scientist, Credit & Fraud Risk Modeling

Kafene

1d • $95,000 - $140,000 • Remote

About The Position

Kafene is revolutionizing the lease-to-own space with cutting-edge AI and machine learning to make flexible lease-to-own accessible to everyone. Our 150-person team spans NYC headquarters, Wilmington, and remote talent across the globe, united by a culture that thrives on collaboration, innovation, and genuine support. We are looking for a Senior Data Scientist who will own the full lifecycle of the ML models that power our credit risk decisions. Reporting directly to the VP of Risk, you'll design, build, deploy, and monitor the models that determine how we approve customers, set credit amounts, predict defaults, and forecast losses. You'll work closely with cross-functional partners across risk, engineering, finance, and sales, and you'll have the rare opportunity to shape both the technical infrastructure and the business strategy behind it.

Requirements

• Master's or PhD in a quantitative discipline: Statistics, Mathematics, Data Science, Econometrics, or a related field.
• 5+ years working as a Data Scientist or ML Engineer with a specific focus on predictive modeling, ideally in credit risk, fraud detection, or financial analytics.
• Experience deploying models that affect real credit or lending decisions.
• Advanced Python for statistical modeling and ML.
• Strong SQL for data extraction and feature construction.
• Deep expertise in ML algorithms for structured/tabular data: gradient boosting, ensemble methods, regression models, decision trees, and AutoML frameworks.
• Prior experience in consumer lending, fintech, or financial services is highly preferred.
• Hands-on experience with model risk governance frameworks and working alongside validation teams (familiarity with SR 11-7).
• Ability to explain complex models to non-technical stakeholders and translate business needs into technical problems.

Nice To Haves

• A software engineering background alone won't be the right fit.

Responsibilities

• Mine internal and external datasets to engineer high-signal features (DTI, PTI, payment behavior, account balance patterns) that directly improve the predictive power of production credit models.
• Own the end-to-end development of strategic credit risk models, including approval amount sensitivity models, credit line optimization, and loss forecasting.
• Source, clean, and transform messy real-world financial data into modeling-ready datasets.
• Evaluate third-party data vendors and scoring products, leading cost-benefit analyses and making integration decisions.
• Apply new techniques from the ML literature to real credit risk problems that ship to production.
• Partner with engineering to implement models into production accurately and efficiently, defining model validation standards and pushing for faster, more repeatable deployment.
• Monitor model performance in production, leading recalibration and redevelopment when performance drifts.
• Navigate model risk governance, regulatory requirements, and data vendor usage policies, ensuring good documentation.
• Translate business questions from risk, finance, and sales into modeling problems and explain solutions in plain language.

Benefits

• Competitive salary
• Coverage for 80% of medical, dental, and vision insurance costs, including for spouse, children, and other dependents.
• 401k plan
• Flexible paid time off days starting from day one.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior