Staff Product Manager - AI (Data & Analytics)

Pearly•Atlanta, GA

2d•$180,000 - $210,000

About The Position

Pearly is a high-growth B2B SaaS and payments company looking for builders to help shepherd the next stage of growth. We are a lean company, allowing for building from a clean slate with process, technology, and AI to accelerate growth and productivity. We are a team of high-talent, high-integrity people who enjoy building and competing, honing our craft, and improving daily. We care about good outcomes and how we achieve them with smart, passionate people who hold each other to a high standard, move fast, and take pride in their work. This role will own AI at Pearly, built on the foundation of our Data & Analytics surface, which includes reporting, dashboards, and financial intelligence. The goal is to evolve this foundation into an intelligence layer that not only shows customers what happened but also anticipates what's next and acts on their behalf. This involves developing descriptive intelligence, predictive intelligence, and agentic AI to automate actions like prioritizing outreach or triggering workflows for collections. The role requires a strategic thinker who can operate independently on ambiguous, high-stakes problems, set direction for the team, and elevate product craft. The ideal candidate will be comfortable defining multi-quarter AI roadmaps and also delving into technical details like schema and query specifications. While data and AI are the core focus, the influence will extend to shaping Pearly's overall product strategy and roadmap, including features across platform domains like Payments and Integrations. This is a role for someone who wants to operate at a high altitude across the entire product, not a narrowly scoped position.

Requirements

7+ years in product management, including time owning a data, analytics, reporting, or BI product at a staff or equivalent senior-IC level, ideally at a high-growth B2B SaaS company.
Ability to run an area with little oversight and improve the skills of surrounding PMs by example.
Fluent in relational databases and SQL.
Comfortable reasoning about data models and schema design.
Ability to hold credible, detailed conversations with engineers about data structure and serving.
Experience scoping and shipping AI-powered features.
Understanding of the current AI toolkit to prioritize its application.
Knowledge of what it takes to make an AI feature reliable.
Experience evaluating and earning trust in systems that act autonomously.
A track record of building dashboards and reporting that users actually utilize.
Proven ability to turn complex data into actionable decisions.
Ability to set strategic direction and define schema, write specifications, and pressure-test dashboards or agents.
Experience shaping strategy and roadmap beyond immediate mandates.
Experience owning features that span across multiple product domains.
Strong commercial instincts; treating data and AI as products with value propositions and prices.
Experience helping to package and monetize data or AI products.
Exceptional discovery and communication skills.
Ability to earn trust with stakeholders like CFOs and VPs of RCM to understand their needs.
Effectiveness in rallying Sales, CS, and Product Marketing around product initiatives.
Comfortable segmenting across buyers from single practices to enterprise DSOs.

Nice To Haves

Experience in dental, healthcare, RCM, or similar industries.
Background building analytics or reporting for finance, RCM, or operations personas.
Hands-on experience with the modern data stack (warehouses, transformation, BI tooling).
A point of view on build-versus-buy decisions for data tooling.
A track record of taking a data or analytics capability from a feature to a revenue-generating product line.
Direct exposure to agentic AI, autonomous or semi-autonomous workflows, and human-in-the-loop design.
Appetite to go deep into agentic AI.

Responsibilities

Own the dashboards, reporting, and insights that help RCM leaders, finance leaders, operations leaders, and office managers make better decisions and run better workflows.
Understand the current reporting surface, customer reliance, and shortcomings, then transform raw data into decision-grade views for various user types.
Own the roadmap for the intelligence layer, driving it from predictive models and signals to agentic AI that takes action on the practice's behalf.
Develop AI features that generate prioritized worklists, draft and trigger outreach, flag anomalies, and take the next best step with human-in-the-loop controls.
Determine which AI features earn autonomy, how to evaluate and trust them, and how to introduce them to customers to provide leverage, not risk.
Deliver insights, patterns, and recommendations for Pearly's internal product, sales, and CS teams to add value to customers.
Monitor key metrics to flag anomalies, surface shifts in A/R collection volume, and identify opportunities for intervention.
A/B test outreach sequences to optimize A/R collection rates based on various factors.
Amplify and extend the value of Pearly's products across the customer journey, making the impact legible to customers and the company.
Collaborate with engineering on the data model and drive PMS integrations.
Bring technical judgment to data pipelines, APIs, data transformation, curation, and storage.
Make decisions on real-time versus batch processing for data.
Ideate, discover, and champion new data, analytics, and AI features and products.
Determine the potential of unique patient balance and payment-behavior data, including its development into a product line with a value proposition and revenue path.
Partner with Product Marketing and Sales on positioning and pricing for new data and AI products.
Conduct discovery directly with financial data stakeholders (CFOs, VPs of RCM, practice owners, DSO operators) to translate needs into a roadmap.
Ensure product development is grounded in real customer demand.
Partner closely with Product, Engineering, Sales, Customer Success, and Product Marketing to ensure successful product development and adoption.
Pull reporting signals from CS, work with Sales and Product Marketing on packaging and positioning, and ensure releases are supported by sales and support teams.