San Francisco, California
Sitting at the intersection of technology and finance, we are an innovative technology underwriting startup managing a credit portfolio of $2.5BN+ on behalf of our investors, many of whom are non-profits, educational endowments, and pension funds. We combine quantitative research-machine learning and data science, software engineering, and rigorous scientific investigation-to build credit portfolios that produce strong and consistent yields across business cycles.
Our firm is 30+ professionals working in San Francisco (HQ) and remote locations. We are passionate, hard-working, relentlessly-resourceful, impact-focused individuals. We deeply value intellectual curiosity, creative idea generation, empathy, and close collaboration. We have (currently virtual) coffee hours, game nights, and team get-togethers. Company events are inclusive and fun, with expeditions to food trucks, Michelin-starred local restaurants, and annual retreats featuring hiking and cooking. About the role: A unique aspect of this position is you may work alongside every person on our team: data engineers, colleagues in finance and operations, investor relations and sales, capital markets and partnerships as well as the firm’s leadership. Your job is to grow firm revenue by increasing qualified purchasing of loans which you’ll do by applying Theorem’s proprietary machine learning models to analyze large datasets of loan data from prospective and existing lending partners. Applicants must be authorized to work in and currently living in the United States, preferably in the Bay Area, or New York or Los Angeles metro areas. Responsibilities:
What you’ll gain:
TBCSQL, Python, Data Modeling, Machine Learning, Data AnalysisSQL, Python, Data Modeling, Machine Learning, Data Analysis, Git, Unix