Python · Java · Kubernetes · Docker · AWS
ABOUT THE ROLE
Build and operate production software that translates financial risk methodologies into reliable scores. This role partners with financial engineering and analytics teams, with a focus on scoring integrity and the broader analytical systems that support the product.
WHAT YOU'LL DO
- Implement and maintain risk models and scoring calculations as reliable, scalable production code.
- Translate documented methodologies into code and raise questions when requirements are ambiguous.
- Design scoring jobs to be repeatable and safe to rerun, and improve their performance as data volumes grow.
- Develop a reference-set validation harness that compares results against adjudicated data and runs in CI for model or taxonomy changes.
- Report validation coverage and drift in a way that supports investigation and model improvements.
- Diagnose live scoring issues across ingestion, application code, data quality, methodology, and customer-facing outputs.
- Contribute to maintainable, modular analytics architecture, tests, code review, and production engineering practices.
- Support financial-data migrations and backfills with tested recovery plans, and contribute across adjacent analytical areas over time.
WHAT WE'RE LOOKING FOR
- At least 5 years of experience building and maintaining production software in established codebases with tests, code review, and CI.
- Experience building large-scale systems and working with high-volume data, data adapters, and web scrapers.
- Hands-on experience implementing risk models, including volatility, correlat