About the Role
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.
What You'll Do
- Create accurate and complete platform term sheets that will allow investment leaders to make business decisions aligned with our target investment profile for our funds — you'll map raw messy data into a useable format to get quick but confident estimates of performance
- Perform robust and quick analysis of multiple potential and existing lending partners and platforms — ranging from unsecured consumer loans to adjacent asset classes
- Research and provide insights about borrowers, loans, and portfolio performance that inform and support teams across the firm — empowering Investor Relations communications as well as due diligence assessments and risk management decisions
- Create templates, tools and automation geared to systematize platform ingestion process for greater speed and accuracy
What You'll Gain
- Mentorship by a senior researcher — a highly technical research and business leader
- Collaborative partnership with data engineers, partnerships and capital markets professionals, investor relations and sales colleagues, as well as many other operational areas
- You'll learn and develop business expertise in unsecured consumer lending and adjacent asset classes, underwriting, and credit risk default modeling
- You'll have the opportunity to learn about business strategy and execution, platform partnerships, and investment portfolio construction
- Your intellectual curiosity and hard work will be welcome contributions to our culture of knowledge sharing, transparency, and shared fun and achievement
What We're Looking For
- 2-5+ years hands-on data analysis experience in full-time professional, data-heavy and analysis-focused role
- Demonstrated knowledge of statistics — primarily probabilities and key aspects of survival analysis
- Basic machine learning models and hands-on data analysis
- Machine learning — primarily classification, model fit & evaluation
- Math savvy and analysis intuition and sense
- Technical competence in SQL, python
- Basic experience with git, unix terminals
- Preferred academic background: technical undergrad degree — CS/stats/math/physics preferred; or strong evidence that demonstrates the candidate’s strength in math+CS
- Located in the US