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Implement and maintain risk models and scoring calculations as scalable production code. Diagnose live scoring issues and contribute to modular analytics architecture and testing practices.
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.
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.
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, correlation, concentration, and tail measures, or working with options, structured products, and derivatives.
Production experience with Python and Django, plus a quantitative or technical background or equivalent demonstrated experience.
Knowledge of financial instruments and US markets, including classification, scoring factors, and proxies for instruments without historical data.
Experience with automated solutions, reference-set or golden-data validation, and production financial-data migrations.
Ability to explain analytical methods and scoring results clearly, including in documentation suited to audit or enterprise review.
Compensation: $4,000 to $8,000 USD. Visa sponsorship is not available.
Remote, with the primary location in India. Remote candidates in Latin America may also be considered.
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