Senior Data Scientist - Remote

Overview

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-powered data 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 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.

In Short

• Partner with Product, Engineering, and other stakeholders to 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
• Develop robust, scalable, and efficient models, balancing algorithmic complexity against interpretability, business needs, and delivery timelines
• Engage in initiatives like using NLP/LLMs for transaction classification and predicting loan defaults
• Work collaboratively across teams to ensure alignment and clarity in project goals

Requirements

• 5+ years of professional experience building and deploying machine learning models in a production environment
• Bachelor’s or Master’s degree in a quantitative discipline (e.g., Computer Science, Statistics, Math, Engineering)
• Full stack data-science experience with production ML models
• Strong communication skills to present complex technical topics
• Deep understanding of statistics, probability, and machine learning algorithms
• Expert-level programming skills in Python and proficiency with data science libraries
• Excellent SQL skills and experience with large data warehouses
• Experience with CI/CD, shell scripting, Git/version control, and cloud infrastructure

Benefits

• Competitive salary and equity
• Remote-first work environment
• Opportunities for skill growth and ownership of work
• Inclusive workplace culture
• Supportive team environment focused on mission-driven work