Lead Credit & Risk Data Science / Analytics

ocrolusinc; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Ocrolus is at the intersection of AI and fintech, building an AI-driven analytics platform that processes credit applications for lenders. The Small Business team leads data products, predictive models, and decisioning tools using large internal and partner datasets to deliver insights that improve credit and risk decisions.

You will partner with product, engineering, and revenue teams to bring new analytics products to market.

Qualifications

• 7+ years of professional experience in risk management, analytics, and/or data science.
• Experience with LLMs and cutting-edge AI tools to create novel products and solutions
• Full stack data-science/analytics: ideating, building, deploying, monitoring, and maintaining production ML models
• Strong programming skills in Python and data-science libraries such as pandas and scikit-learn
• Excellent SQL skills and working with large data warehouses like Snowflake or Postgres
• Bachelor's or Master's degree in a quantitative field

Responsibilities

• Analyze large, diverse datasets around business cash flow, credit, and marketplace dynamics to extract insights and identify product opportunities
• Partner with Product, Engineering, and leadership to develop analytical data products
• Lead data science efforts to research and develop new data and decisioning products
• Interact with clients as SME on small business credit and Ocrolus analytics suite
• Develop scalable models balancing complexity and interpretability with customer needs and timelines
• Own end-to-end lifecycle of data science models from exploration to deployment and monitoring

Skills

Risk analytics

Data science

Python

SQL

Pandas

scikit-learn

Hugging Face

Communication

Education

Bachelor's or Master's in a quantitative discipline

Tools

Snowflake

Postgres

Pandas

scikit-learn

Hugging Face

Job description

Come build at the intersection of AI and fintech. At Ocrolus, we're on a mission to help lenders automate workflows with confidence-streamlining how financial institutions evaluate borrowers and enabling faster, more accurate lending decisions.

Our AI workflow and analytics platform for lenders 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 our human-in-the-loop verification engine, Ocrolus captures data from financial documents with over 99% accuracy. Thanks to our advanced fraud detection and comprehensive cash flow and income analytics, our customers achieve greater efficiency in risk management, and provide expanded access to credit-ultimately creating a more inclusive financial system.

Trusted by more than 400 customers-including industry leaders like Better Mortgage, Brex, Enova, Nova Credit, PayPal, Plaid, SoFi, and Square-Ocrolus stands at the forefront of AI innovation in fintech. Join us, and help redefine how the world's most innovative lenders do business.

The Small Business team at Ocrolus uses our massive and unique dataset of cash flow, credit, and financial data from the market's most sophisticated lenders to build high-quality data products empowering lenders to make better credit, fraud, and operational risk decisions. This role will lead our efforts to mine internal, client, and partner data for unique insights and develop data products, predictive models, and analytical tools that leverage the power of the Ocrolus network. You will analyze large and unique datasets, interact as a subject matter expert with clients and prospects, and work with excellent colleagues in product, engineering, and revenue to bring transformational data products to market. If you are a curious, high-agency analytics leader who wants to leverage your experience in SMB credit risk and strong technical skills to drive outsize impact, we want to talk to you!

What you'll do

• Analyze large, diverse, and unique datasets around business cash flow, financial health, credit, marketplace dynamics, and repayment performance to unearth powerful insights and identify compelling product opportunities.
• Partner with Product, Engineering, senior management, and other stakeholders to develop and commercialize analytical and data products that will drive impact for our clients and gain adoption in the market.
• Lead Ocrolus' analytical and data science efforts to research and develop new data and decisioning products, including mentoring colleagues from a business and technical standpoint.
• Interact with clients and prospects as a subject matter expert on small business credit and the Ocrolus suite of analytics and decisioning products.
• Develop robust, scalable, and efficient models, thoughtfully balancing algorithmic complexity against interpretability, customer needs, and delivery timelines.
• Translate ambiguous business challenges into well-defined data science problems
• Own the end-to-end lifecycle of data science models, from data exploration and feature engineering to deployment, monitoring, and continuous improvement in production

Examples of SMB analytics initiatives include: using agentic pipelines to enhance transaction classification, training gradient boosting trees to predict loan default probability and loss-given-default based on transactional cash flow data, building entity resolution systems to match financial data across time with a specific merchant, mining massive internal and partner datasets to build agentic fraud detection systems, resolving data signals from across the Ocrolus network to build a comprehensive and contextualized profile of small business financial health and debt capacity

What you'll bring

• 7+ years of professional experience in risk management, analytics, and/or data science, building decision strategies and building/deploying predictive models in a production environment
• Significant knowledge of small business credit, including underwriting, pricing, and portfolio management
• Expertise and hands-on curiosity with using LLMs and cutting-edge AI tools to create novel products and solutions
• Full stack data-science/analytics experience: ideating, building, deploying, monitoring, and maintaining production ML models that solve real-world needs
• Deep understanding of statistics, probability, and machine learning algorithms
• Strong software engineering and data engineering fundamentals. Excellent programming skills in Python and proficiency with core data science libraries (e.g., pandas, scikit-learn, Hugging Face)
• Excellent SQL skills and comfort working with large and complex data warehouses (Snowflake/Postgres)
• Bachelor's or Master's degree in a quantitative discipline (e.g., Computer Science, Statistics, Math, Engineering)
• The ability to communicate and present complex technical topics and results to various audiences. Sk