The opportunity
Centralized home-office equipment ordering
What you'll do
Own credit risk strategy for areas like model prototyping, credit limits, payment speed, collections, etc.
Use SQL, quantitative reasoning, and credit risk judgment to investigate: patterns, size opportunities, define policy changes, and pressure-test recommendations.
Build the first useful version when the workflow does not exist: a tool, app, dashboard, agent, notebook, QA loop, monitor, or decisioning process.
Use AI tools every day to move faster on research, analysis, coding,: synthesis, writing, verification, and follow-through.
Build AI into credit risk workflows: feature exploration, policy monitoring, case review, exception handling, decision support, documentation, and human-in-the-loop QA.
Investigate new data sources and model features; evaluate signal quality,: coverage, failure modes, and how they would change credit decisions.
What they're looking for
- Make ambiguous credit risk decisions within your surface area, balancing: loss, customer experience, operational burden, growth, compliance, and risk-adjusted returns.
- Partner with Product, Engineering, Design, to execute and build the risk management infrastructure
- Minimum 2 years of experience in credit risk management or quantitative strategy role
- Minimum 2 years of experience using SQL or Python for data retrieval and manipulations
