Director, AI & Data Science

(This role is based in Trepp's NYC office and follows a hybrid work schedule)

Trepp is searching for an individual to lead our Data Science & Modeling team within Trepp's Engineering department. This position reports directly to the CTO. In this role, you will be responsible for leading, growing, and charting the future vision for this group of data scientists and engineers.

You’ll be staying hands-on with the team that builds the AI-powered product features, statistical models, and machine learning capabilities behind Trepp's products across structured finance (CMBS, CLO), commercial real estate (CRE), and banking & lending product lines.

We provide a collaborative team environment where our technologists work closely with Product, subject matter experts, and other technology teams and are empowered to impact the organization through leadership, creativity, and innovation. Trepp values individuals who are not afraid to propose new ideas and challenge the status quo.

Beyond leading the team, this role will be a key voice in shaping Trepp's AI strategy — both how we bring AI-powered features and workflows to customers through our products, and how we drive AI adoption internally across the engineering organization and the broader company.

Responsibilities:

• Be a hands-on leader of the Data Science & Modeling team. This role is expected to lead & manage the team, but will be hands-on and involved in model design, validation, and technical review.
• Own the technical roadmap for Trepp's modeling capabilities, setting standards for model development, validation, and deployment across CRE, CMBS, CLO, and banking data products.
• Recruit, manage, mentor, and develop a team of data scientists and engineers, including hiring and performance management.
• Partner with technical leads across other engineering domains (full stack, data pipelines, operations) to ensure models are built on solid infrastructure and shipped into production cleanly.
• Partner with Sales and Product teams on strategic client conversations to articulate Trepp’s AI and data science capabilities and support product adoption.
• Help define Trepp's AI strategy in partnership with the CTO, covering both customer-facing AI features/workflows in our products and internal AI adoption across the company.
• Identify and prioritize high-value AI use cases (e.g., agentic workflows, LLM-powered features, automation of modeling and reporting workflows) and translate them into a roadmap engineering can execute against.
• Act as a technical advisor on AI capabilities, tradeoffs, and risk (accuracy, explainability, data governance) for both product and executive stakeholders.
• Drive internal AI tooling adoption, helping other teams across the company use AI effectively in their own workflows.
• Consult senior-level stakeholders across the organization to identify business and technology needs and optimize the use of data science and AI tools.
• Evaluate new modeling techniques, tools, and data sources, and make the call on what's worth adopting.
• Communicate technical concepts, model performance, and AI capabilities/limitations clearly to non-technical executives and stakeholders.
• Required Skills: Bachelor's Degree in Computer Science, Statistics, Mathematics, Data Science, or equivalent field. Advanced degree preferred.
• Minimum 8 years of experience in data science, quantitative modeling, or applied machine learning, including hands-on model-building work.
• Minimum 4 years of experience in leading and running an engineering team. You will own team roadmap, planning, and team & individual goal setting.
• Expertise in Python and the data science toolkit ecosystem (numpy, scikit-learn, pandas), plus strong SQL skills.
• Demonstrated experience shaping or executing an AI strategy — not just using AI tools, but making decisions about what to build, buy, or adopt and why.
• Experience deploying production AI systems using cloud-native technologies, containerization, and orchestration platforms.
• Working knowledge of modern LLM/agentic AI concepts and tradeoffs (RAG, tool use, evaluation, guardrails), LLMOps and how they apply to real products.
• Strong interpersonal skills and ability to effectively communicate with teams across the entire organization.
• Preferred Skills: A drive to work on financial data systems & pipelines, including experience working with structured finance or commercial real estate datasets.
• Experience with MLOps practices to manage model lifecycle, versioning, deployment, and monitoring using best practices, APIs, and tooling.
• Prior experience building or scaling an internal AI tooling/adoption program, not just customer-facing AI.
• Background in Financial Services, commercial real estate or related industry.
• Familiarity with Atlassian Product Suite (Jira/Confluence), AWS Cloud, and GitHub-based engineering workflows.