SMB Analytics & Data Science Lead
Ocrolusinc · New York, United States
About this role
**Come build at the intersection of AI and fintech at Ocrolus.** Ocrolus helps lenders automate workflows with confidence—streamlining how financial institutions evaluate borrowers and enabling faster, more accurate lending decisions. Our AI workflow and analytics platform is trusted at scale, processing nearly **one million credit applications every month** across small business, mortgage, and consumer lending. By integrating state-of-the-art open- and closed-source AI models with a human-in-the-loop verification engine, Ocrolus captures data from financial documents with **99%+ accuracy**—supporting fraud detection and comprehensive cash flow and income analytics to improve risk management and expand access to credit. --- ## Role: SMB Analytics & Data Science Lead The Small Business team uses a massive dataset of cash flow, credit, and financial data from sophisticated lenders to build high-quality data products that help lenders make better **credit, fraud, and operational risk** decisions. In this role, you’ll lead efforts to mine internal, client, and partner data for unique insights and develop **data products, predictive models, and analytical tools** leveraging the Ocrolus network. You’ll analyze large datasets, act as a subject matter expert with clients and prospects, and partner with Product, Engineering, and Revenue to bring transformational products to market. --- ## What you’ll do - Analyze large, diverse, and unique datasets across **business cash flow, financial health, credit, marketplace dynamics, and repayment performance** to uncover insights and identify product opportunities. - Partner with Product, Engineering, senior management, and stakeholders to develop and commercialize analytical and data products. - Lead Ocrolus’ analytical and data science efforts—researching and developing new decisioning and data products, and mentoring colleagues. - Serve as a subject matter expert on **small business credit** and Ocrolus analytics/decisioning products. - Build robust, scalable, efficient models—balancing complexity vs. interpretability, customer needs, and delivery timelines. - Translate ambiguous business problems into well-defined data science work. - Own the end-to-end lifecycle of models: **exploration → feature engineering → deployment → monitoring → continuous improvement**. - Examples of initiatives include: - Agentic pipelines to enhance transaction classification - Gradient boosting models to predict loan default probability and loss-given-default - Entity resolution to match financial data across time to specific merchants - Agentic fraud detection using internal and partner datasets - Building contextual small business financial health and debt capacity profiles from network signals --- ## What you’ll bring - **7+ years** experience in risk management, analytics, and/or data science—building decision strategies and deploying predictive models in production. - Strong knowledge of **small business credit** (underwriting, pricing, portfolio management). - Hands-on curiosity with **LLMs and cutting-edge AI tools** to create novel products. - Full-stack data science/analytics experience: ideate, build, deploy, monitor, and maintain production ML. - Deep understanding of **statistics, probability, and machine learning**. - Strong software + data engineering fundamentals; excellent **Python** skills and familiarity with tools like **pandas, scikit-learn, Hugging Face**. - Excellent **SQL** and c
Listing freshness
CronJobs last confirmed this listing 1h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.