Risk Data Scientist

LendingHome is reimagining the mortgage process from the ground up by combining innovative technology with an experienced team. Our goal is to create a seamless, transparent process for homebuyers, real estate professionals, and investors.

LendingHome is seeking a talented and highly analytical Risk Data Scientist to join the Risk team in our effort to reinvent mortgage. You will tackle challenging business problems, including risk modeling, asset valuation, process optimization, and price sensitivity. An ideal candidate should be able to utilize advanced data manipulation and machine learning techniques to solve complex business problems. You’ll also have to work cross-functionally with Product, Engineering, Capital Markets, and many other departments to co-pilot different initiatives. If you’re keen on joining a dynamic company and working on intellectually challenging problems in a fast-paced environment, LendingHome is the place for you.

* Develop and maintain innovative models for mortgage underwriting. This requires thorough statistical analysis of the underlying data and an understanding of the various macroeconomic and risk factors that impact the credit quality of borrowers * Develop models for doing portfolio analytics, such as loss forecasting, collection likelihood, and fraud detection * Continually explore and iterate on statistical models and features to advance our understanding of key underlying business drivers * Perform in-depth, rigorous ad-hoc analysis to derive meaningful insights executive management can clearly act upon * Define, create, and improve metrics and dashboards that precisely and accurately measure the health of the business * Drive improvements in business outcomes by testing new and different strategies through systematic planning and execution of experiments * Develop analytical tools to support other teams * Work cross-functionally to enhance our data capture process and infrastructure

* Bachelor’s degree in Math, Statistics, Computer Science, Economics, Finance, Engineering, Physics or a related quantitative discipline * Excellent grasp of fundamentals in statistics and probability * Solid understanding of machine learning techniques * Strong programming skills in R or Python * Team player with strong interpersonal skills * Ability to partner, collaborate, and communicate well with a diverse set of colleagues, both technical and non-technical, at all levels of the organization * A resourceful and pragmatic approach to problem solving and recognition that the best solutions are sometimes the simplest **Preferred Qualifications** * Advanced degree (Master’s or PhD) in a quantitative discipline * Experience with Monte Carlo simulation and Bayesian statistics * Experience using SQL * Experience in a modeling group at a commercial bank, investment bank, consulting firm, or technology company * Experience with residential mortgage models, especially with mortgage underwriting, scoring, default, or prepayment models * Experience with fraud detection models