Staff Applied Scientist

Role overview Research and improve machine learning models used to assess unsecured loan applications. You’ll test modeling ideas, evaluate how they affect credit decisions, and work with engineering partners to move validated improvements into production while maintaining analytical rigor and responsible oversight.

Responsibilities - Investigate machine learning and statistical methods to improve underwriting model predictions. - Design, implement, and evaluate model changes using structured experiments and validation. - Analyze model performance and downstream decision effects to check that changes are reliable. - Work with engineering teams on technical review, implementation, and deployment. - Document methods and explain findings as clear recommendations and production-ready solutions.

Requirements - Graduate degree in a quantitative discipline such as statistics, mathematics, physics, econometrics, operations research, or computer science. - At least two years of experience in machine learning, statistical modeling, or applied quantitative research. - Experience developing and assessing models with Python. - Knowledge of probability, statistics, and machine learning methods. - Experience designing experiments or validation analyses to measure model accuracy, reliability, or predictive performance.

Nice to have - Doctorate in a quantitative field. - Familiarity with supervised learning, model evaluation, and feature engineering. - Experience with large or complex datasets and turning research into implemented solutions. - Ability to balance research speed with rigor, reliability, and responsible decisions. - Clear communication and cross-functional collaboration skills.

Benefits and work setup - Remote role available in the United States or Canada, excluding Quebec, with East or West Coast time zone alignment. - Regular in-person team gatherings are expected; many teams meet once or twice per quarter for several consecutive days. - Full-time benefits include health coverage, retirement savings support, paid leave, and allowances for wellness and work tools. Compensation may include bonus and equity.