Senior Credit Machine Learning Scientist
Mercury
Build lending models at Mercury using Python, SQL, and proprietary business data to inform small business credit decisions. Production deployment and monitoring are central.As a Senior or Staff Data Scientist, you will own the inference layer for Mercury’s small business lending program. You will work with Credit, Product, and Engineering across transaction classification, forecasting, and uncertainty. The work turns bank transactions, storefront sales, and financial reporting into defensible views of business health.Key Responsibilities:
Build transaction classification and recurring cash-flow detection modelsEstimate annual revenue and forecast seasonal business performanceDeploy production models with observability, monitoring, and testsPartner with Credit on underwriting policy and uncertaintySet technical standards for machine learning in CreditRequirements:
Three or more years building machine learning modelsAt least one year in lending or credit algorithmsStrong Python, production-grade services, and SQL experienceExperience working comfortably in a data warehouseAbility to explain models across credit, product, and engineeringApply credit modeling, Python, SQL, and production machine learning expertise to Mercury’s small business lending infrastructure.
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Build transaction classification and recurring cash-flow detection modelsEstimate annual revenue and forecast seasonal business performanceDeploy production models with observability, monitoring, and testsPartner with Credit on underwriting policy and uncertaintySet technical standards for machine learning in CreditRequirements:
Three or more years building machine learning modelsAt least one year in lending or credit algorithmsStrong Python, production-grade services, and SQL experienceExperience working comfortably in a data warehouseAbility to explain models across credit, product, and engineeringApply credit modeling, Python, SQL, and production machine learning expertise to Mercury’s small business lending infrastructure.
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Vacancy posted 55 minutes ago
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