This is a fully remote position, open to applicants in United States, +4 more locations.

📋 Description

• Develop and manage models for the small business lending program, encompassing transaction classification, detection of recurring inflows/outflows, annual revenue estimation, seasonal forecasting, and anomaly identification.

• Transform bank transaction data, storefront sales, and other complex data streams into a reliable assessment of business health.

• Implement models in production with observability, monitoring, and testing protocols.

• Collaborate with the Credit team on underwriting policies, including required data, follow-up details, and uncertainty quantification.

• Work alongside the Product team on determining principal amounts, pricing strategies, and repayment conditions.

• Evaluate how predictive modeling can enhance the underwriting process.

• Establish the technical standards for machine learning within the Credit department.

⛳️ Requirements

• Over 7 years of experience in building machine learning models.

• Developed models that influenced automated decisions involving financial stakes.

• Proficient in production-grade Python.

• In-depth knowledge extending beyond classification models, including time series and forecasting, anomaly detection, and natural language processing models.

• Expertise in deep learning, transformers, and large language models (LLMs).

• Strong SQL capabilities and familiarity with data warehouse environments.

• Ability to articulate model concepts to credit officers, model validators, project managers, and engineers.

• Capacity to establish modeling standards for fellow data science professionals.

• A quantitative degree or equivalent experience gained through alternative pathways.

• Direct experience with modeling based on bank transaction data (preferred).

• Background in small business lending or business credit cards (preferred).

• Experience with revenue-based financing, merchant cash advances, or similar financial products (preferred).