Senior Applied Scientist, Credit Risk

Design, build, and optimize machine learning models for credit risk decisioning.

• •We're looking for a Senior Applied Scientist to help drive the future of credit applied science at Ramp.
• •In this role, you will design, build, and optimize the models that power our credit risk systems, helping us make faster, smarter, and more scalable risk decisions for our customers.
• •Key Responsibilities Design, build, and optimize machine learning models that support credit risk decisioning and portfolio management at Ramp Own the full applied science development lifecycle, from data exploration and feature development to model prototyping, deployment, monitoring, and iteration Investigate and evaluate new data sources, including structured and unstructured data, and integrate them into credit models where appropriate Develop backtesting, validation, and monitoring frameworks to evaluate model performance and business impact Apply methods from machine learning, statistics, causal inference, optimization, and economics to solve core business problems Requirements Bachelor's degree or above in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields 5+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 3+ years of industry experience with a PhD Strong familiarity with the mathematical fundamentals of advanced statistics, machine learning, optimization, and/or economics Experience working with large datasets using Python and SQL Strong Python experience across exploratory data analysis, predictive modeling, and applied machine learning, using tools such as NumPy, pandas, scikit-learn, PyTorch, or similar libraries