Senior Product Manager, Data & AI Products (R14077)

Job Description

POSITION OVERVIEW

We're looking for a Senior Product Manager to own and scale Oportun's internal data products and lead our Gen AI analytics initiative. This role sits at the intersection of data infrastructure, AI/ML, and product strategy. You'll own critical data products that power Capital Markets, FP&A, and Enterprise Analytics while building the next generation of AI powered data access tools. You'll be building internal products that make Oportun's data more accessible, trustworthy, and actionable. Your users are analysts, data scientists, finance and other business teams, and executives who depend on data to make high-stakes decisions every day. If you're excited by the idea of applying product thinking to data infrastructure and AI systems, and you want to work on problems that span forecasting models, capital markets operations, semantic layers, and agentic AI, this role is for you.

RESPONSIBILITIES

Gen AI Analytics Initiative (OportunResearch)

You'll lead product strategy for OportunResearch, our AI-powered analytics assistant. This means defining the roadmap, working with engineering on agentic capabilities, designing human-in-the-loop workflows, and driving adoption across the org.

Data Products Portfolio

You'll own the product strategy for EDT's core data products:

• Merlin: Our suite of forecasting models powering Collateral Revenue, Fair Value, and related corporate forecasting. You'll drive the roadmap from current state through advanced time-series capabilities.
• Cosmos: Our Capital Markets data platform handling pledging operations, concentration management, and investor reporting.
• HITL Platform: The Human-in-the-Loop system for capturing institutional knowledge, validating AI outputs, and building feedback loops that make our data and AI systems smarter over time.

Semantic Layer & Data Certification

You'll partner with analytics engineering to ensure our semantic layer is comprehensive enough to support AI-powered querying. This means understanding metric definitions, data certification status, and how to expose the semantic layer as an API for AI agents.

What Success Looks Like

In the first 90 days:

• Deep understanding of Merlin, Cosmos, and the HITL platform architecture and roadmaps
• Relationships built with key stakeholders across Capital Markets, FP&A, Risk, and Engineering
• First iteration of OportunResearch product requirements and pilot scope defined

In the first year:

• OportunResearch launched and demonstrating measurable reduction in analyst
• Merlin advanced forecasting capabilities (scenario planning, time-series optimization) in production
• HITL platform operational with feedback loops capturing institutional knowledge
• Clear metrics showing self-service adoption growth and response quality

REQUIREMENTS

Experience:

• 6-10+ years of product management experience, with at least 3 years focused on data products, analytics platforms, or AI/ML systems
• Track record of shipping data-intensive products in complex enterprise environments
• Experience working with data engineering, analytics engineering, and/or ML engineering teams
• Familiarity with the modern data stack (warehouses, semantic layers, BI tools, orchestration)

Technical Fluency:

• You don't need to write production code, but you should be able to read SQL, understand data modeling concepts, and have informed conversations about system architecture
• Understanding of LLMs, RAG patterns, and agentic AI concepts (you don't need to be an ML engineer, but you need to understand what's possible and what's hype)
• Comfort with ambiguity in fast-moving technical domains

Product Skills:

• Strong product discovery skills: ability to understand user needs, synthesize research, and define problems worth solving
• Ability to write clear product requirements that engineering teams can execute against
• Experience defining and tracking metrics that matter, not vanity metrics
• Skill at managing competing priorities and making tradeoffs explicit

Collaboration & Communication:

• Ability to influence without authority across engineering, analytics, and business teams
• Clear written and verbal communication, especially when explaining technical concepts to non-technical stakeholders
• Comfort presenting to executives and defending product decisions

Mindset:

• You're energized by hard problems that don't have obvious solutions
• You're comfortable building for internal users who have high expectations and strong opinions
• You believe that data products deserve the same rigor and craft as consumer products
• You're not precious about your ideas; you'd rather be right than be the one who came up with the answer

Nice to Have

• Experience in financial services, fintech, or capital markets
• Experience building AI/ML products, especially LLM-powered applications
• Familiarity with Databricks, dbt, or similar platforms
• Background in analytics or data science before moving into product management

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