Data Scientist

Senior AI Engineer

Hybrid - Washington D.C. (preferred) or New York, NY

About The Role 

We are seeking a highly motivated and innovative Senior Data Scientist (AI/ML) to join our brilliant team of analytics professionals and developers, supporting the cutting-edge development of credit scoring models, generation of unique insights, and delivery of transformative technologies rooted in innovative value propositions.

In this role, you will be essential to credit score model innovation, credit and open banking related  research initiatives, pilot program analyses with lenders and fintech partners, and ongoing model monitoring and reporting processes. You’ll bring your expertise in AI/ML and GenAI/Large Language Models (LLMs) to advance our use of structured and unstructured data to deliver new products and insights.

You’ll partner cross-functionally to deliver scalable AI-powered products and solutions that redefine how consumers engage with credit — ensuring our models are accurate, explainable, and aligned with our mission to empower responsible lending and financial inclusion.

Key Responsibilities
• Conduct advanced research on structured and unstructured data, developing insights to support product management and new product development.
• Contribute to the design, development, evaluation, and deployment of machine learning (ML) models, including credit risk and predictive models.
• Serve as the team’s expert on GenAI/LLMs, adapting and fine-tuning models and ensuring explainability and compliance.
• Drive pilot program analyses, including back-testing, rejection inference, and performance analyses using diverse data sets.
• Improve and maintain existing model monitoring processes and develop compelling data visualizations and dashboards to communicate key insights to stakeholders.
• Partner with engineers to operationalize models into production systems, ensuring scalability and resilience at high data and inference volumes.
• Research and apply emerging AI/ML, GenAI/LLM technologies, staying abreast of state-of-the-art methods, tools, and best practices.
• Translate complex analyses into clear, actionable business recommendations for both technical and non-technical audiences.
• Contribute to thought leadership through white papers, presentations, and insights shared internally and externally.

Basic Qualifications
• Master’s or PhD degree in a quantitative field (e.g., Data Science, Applied Mathematics/Statistics, Computer Science, Engineering, Econometrics).
• 3-5 years of professional experience in advanced analytics, AI/ML/LLM, and data science in research and/or corporate environments. • Proficiency in Python for data science and machine learning workflows. • Proven experience with machine learning techniques (classification, clustering, regression, neural networks) for predictive risk and credit modeling. • Strong track record of conducting research, developing analyses, and producing clear and impactful presentations or publications. • Experience delivering insights and solutions that drive business impact. • Experience working in Agile and cross-functional teams.