[Hiring] SMB Analytics & Data Science Lead @Ocrolus Inc.

Role 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.

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.

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.

Qualifications

• 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. Skilled in collaborative and compelling communication with clients and prospects.
• Passion for understanding the “why” of the problem and the impact of solutions on client outcomes.

Requirements

• Experience working with messy, real-world financial data (e.g., bank transaction streams, financial statements, credit reports).
• Portfolio of past data science/analytics accomplishments (including source code).

Benefits

• The full-time salary range for this role is in the range of $230K-270K + equity + benefits. Base pay offered may vary depending on job-related knowledge, skills, experience, and market location.
• Disclosure as required by N.Y.C. Admin. Code §§ 8-102 and 8-107(32) of the full time salary compensation range for this role when being hired into our offices in New York City.

Company Description

We’re a team of builders, thinkers, and problem solvers who care deeply about our mission — and each other. As a fast-growing, remote-first company, we offer an environment where you can grow your skills, take ownership of your work, and make a meaningful impact.

Our culture is grounded in four core values:

• Empathy – Understand and serve with compassion.
• Curiosity – Explore new ideas and question the status quo.
• Humility – Listen, be grounded, and remain open-minded.
• Ownership – Love what you do, work hard, and deliver excellence.

We believe diverse perspectives drive better outcomes. That’s why we’re committed to fostering an inclusive workplace where everyone has a seat at the table, regardless of race, gender, gender identity, age, disability, national origin, or any other protected characteristic.

We look forward to building the future of lending together.