Product Manager - Data Intelligence

Rocket Money•New York, WA

5d•$120,000 - $160,000•Hybrid

About The Position

You'll own the intelligence layer that makes Rocket Money smarter for every member. Working at the intersection of machine learning, AI / LLM, and consumer product, you'll partner with a team of Software Engineers and Machine Learning Engineers to extract financial insights from bank transactions, emails, and receipts — then ship front-end experiences that turn those insights into real money-saving opportunities. This is a partial-platform role: the systems you build will power and enrich features across multiple Rocket Money product teams, as well as supporting your own customer facing features. Define the AI-driven data intelligence roadmap for transaction enrichment, financial insight extraction, and money-saving intelligence — aligning with Rocket Money's broader product vision Define technical problem statements and work with engineers to select the right approach, by mapping engineering the tradeoffs of heuristics, machine learning and LLM approaches to prioritized customer and business outcomes. Partner with Software Engineers and Machine Learning Engineers to develop intelligence systems that leverage both ML models and LLMs to extract structured, actionable insights from bank transactions, emails, receipts, and other financial data Ship customer-facing experiences on top of enriched data — collaborating with Design and front-end engineers to deliver products that surface insights & savings opportunities Build and maintain a monitoring and evaluation system for intelligence outputs — tracking prediction accuracy, extraction quality, insight helpfulness, customer sentiment, and model cost to drive continuous improvement Prioritize trade-offs across model accuracy, inference speed, and cost — particularly as LLM usage scales — to deliver the best member experience within practical constraints Collaborate across Rocket Money product teams to understand how your platform can support and improve their initiatives, features, and OKRs and vice versa

Requirements

4+ years of experience as a product manager building products that use machine learning and/or LLMs to improve product dynamism and deliver intelligent, self-learning user experiences
You have a strong intuition for when to use heuristics vs. traditional ML vs. LLM-based approaches and can articulate the trade-offs in accuracy, latency, and cost to technical and non-technical stakeholders alike
You're comfortable working across the full stack — from front-end interfaces that delight customers to the complex ML pipelines and LLM integrations that power them
You possess a unique combination of technical depth, customer empathy, and strategic thinking , and are energized by operating at the center of machine learning and consumer product
You're a master cross-functional collaborator comfortable working with machine learning engineers, software engineers, designers, data analysts, and other product managers to get things done
You can use data and customer feedback to generate insights, identify opportunities, and tell a story that motivates those around you
You have an owner's mindset — you don't shy away from the hard stuff. You proactively act on problems, and never wait around to be told what to do.
You have a passion for our mission: helping to improve the financial lives of millions of people
Strong analytical skills; competence in SQL and experience with tools for data analysis

Nice To Haves

Experience running LLM evals or building evaluation frameworks for model and extraction quality is a plus
Background in statistics or computer science is a plus
Prior fintech experience is a plus

Responsibilities

Define the AI-driven data intelligence roadmap for transaction enrichment, financial insight extraction, and money-saving intelligence — aligning with Rocket Money's broader product vision
Define technical problem statements and work with engineers to select the right approach, by mapping engineering the tradeoffs of heuristics, machine learning and LLM approaches to prioritized customer and business outcomes.
Partner with Software Engineers and Machine Learning Engineers to develop intelligence systems that leverage both ML models and LLMs to extract structured, actionable insights from bank transactions, emails, receipts, and other financial data
Ship customer-facing experiences on top of enriched data — collaborating with Design and front-end engineers to deliver products that surface insights & savings opportunities
Build and maintain a monitoring and evaluation system for intelligence outputs — tracking prediction accuracy, extraction quality, insight helpfulness, customer sentiment, and model cost to drive continuous improvement
Prioritize trade-offs across model accuracy, inference speed, and cost — particularly as LLM usage scales — to deliver the best member experience within practical constraints
Collaborate across Rocket Money product teams to understand how your platform can support and improve their initiatives, features, and OKRs and vice versa