Senior Data Scientist - Credit and Lending ML

Mercury•Portland, OR

7h•$166,600 - $298,800

About The Position

Mercury is building financial infrastructure for startups and growing businesses and extending credit using proprietary data such as bank transactions, financial reporting, and payroll. The Senior Data Scientist will build and own the inference layer for Mercury’s small business lending program, put models into production with monitoring and documentation, and help Credit and Product determine lending policies and product design. The role partners closely with Credit, Product, and Engineering and helps establish technical standards for machine learning in Credit.

Requirements

At least 3 years building machine-learning models, including at least 1 year working on lending or credit algorithms.
Thoughtful opinions about where machine learning can best improve an underwriting program.
Some professional exposure to deep-learning or transformer models.
Strong Python skills and experience with production-grade services.
Strong SQL skills and familiarity with a data warehouse.
Ability to explain models to credit officers, model validators, product managers, and engineers.
Ability to establish modeling standards for data-science colleagues.
A quantitative degree or equivalent experience.

Nice To Haves

Direct experience modeling bank transaction data.
Experience in small business lending or business credit cards.
Experience with revenue-based financing, merchant cash advances, or similar products.

Responsibilities

Build and own models for the lending program, including transaction classification, recurring inflow and outflow detection, annual revenue estimation, seasonal forecasting, and anomaly detection.
Turn data streams such as bank transactions and storefront sales into a defensible view of a business’s health.
Deploy models into production with observability, monitoring, and tests.
Partner with Credit on underwriting policy, including requested data, follow-up information, and uncertainty measurement.
Partner with Product on lending product design, including principal sizes, pricing, and repayment terms.
Assess where predictive modeling can improve the underwriting program.
Set the technical bar for machine learning in Credit.