Mercury is hiring a remote Senior and Staff Data Scientist Credit and Lending ML!
Mercury is hiring a senior or staff data scientist to shape the machine-learning systems behind its small-business lending program. The role sits at the intersection of credit, product, and engineering, turning raw financial signals such as bank transactions, sales data, and payroll information into reliable views of borrower health and defensible lending decisions. The data scientist will own models from early design through production deployment, including monitoring and documentation, while helping credit and product teams decide where predictive modeling adds real value and where simpler judgment should prevail. This is a remote position with compensation ranges published for both US and Canadian employees.
Key responsibilities
- Design and own models used in underwriting, including transaction categorization, recurring cash-flow detection, revenue estimation, seasonal forecasting, and anomaly detection
- Convert noisy financial data into consistent, explainable indicators of business health
- Put models into production with tests, observability, and ongoing monitoring
- Work with Credit to define data collection, follow-up thresholds, and uncertainty estimates for underwriting policy
- Collaborate with Product on loan sizing, pricing, repayment structures, and other product design choices
- Identify which parts of the underwriting process benefit most from predictive modeling
- Help establish modeling standards and technical direction for data science in Credit
Key requirements
- For Staff: 7+ years building ML models, including systems that informed automated decisions involving financial risk
- For Senior: 3+ years building ML models, with at least 1 year in lending or credit algorithms
- Strong production Python and experience shipping maintainable model services
- Strong SQL and comfort working in a data warehouse
- Depth in areas beyond standard classification, such as time series forecasting, anomaly detection, NLP, deep learning, transformers, or LLMs
- Ability to explain models clearly to credit officers, validators, product managers, and engineers
- Quantitative degree or equivalent practical background
- Nice to have: bank transaction data modeling, small-business lending, business credit cards, revenue-based financing, or merchant cash advance experience
- Seniority: Senior or Staff
- Work mode: Remote
- Salary: US employees: $166,600–$298,800 USD; Canadian employees: $157,400–$282,400 CAD
- Key skills: Python, SQL, machine learning, credit risk modeling, time series forecasting, anomaly detection, NLP, deep learning, transformers, LLMs, data warehouses, production ML, model monitoring, financial data
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