Senior Product Manager, Predictive Insights & Optimization

Ibotta•Denver, CO

7d•$123,000 - $143,000•Hybrid

About The Position

Ibotta is seeking a Senior Product Manager for Predictive Insights & Optimization to lead the development and execution of Machine Learning driven forecasting & optimization models. Your work will include predictive campaign performance, as well as campaign optimization. You will partner closely with Data Science, ML Engineering, Client Analytics, and Revenue teams to drive requirements and success criteria for model inputs, model features, and model outputs. Success is delivering solutions that maximize predictive performance, surface actionable signals that improve campaign performance, and deliver ML-guided products to internal revenue teams and customers. You will define the vision, drive alignment, document the roadmap, and prioritize features of our forecasting and optimization capabilities. This position is located in Denver, Colorado as a hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday). Candidates must live in the United States.

Requirements

5+ years Product Management experience, with at least 2 years in applied ML / ML product management
BA/BS in CS, Engineering, Economics, Math, or related field required
Experience building Machine Learning ecosystems and production ML products at scale
Strong quantitative skills with the ability to design tests, analyze large datasets, and draw actionable insights
Up-to-date knowledge of ML best practices, modeling tradeoffs, and MLOps considerations
Proven ability to become a subject matter expert in your domain and represent strategy to senior leadership
Strong cross-functional collaboration skills and comfort navigating high-growth, ambiguous environments
Excellent communication skills across visual, written, and verbal mediums

Responsibilities

Own the Machine Learning product roadmap for forecasting and optimization to maximize business impact
Lead development of pre-flight and in-flight prediction models and tooling that inform campaign design and real-time optimization
Partner with Data Science and ML Engineering to build and maintain scalable, reliable, and secure ML infrastructure and platform
Define model inputs, feature priorities, experiment designs, and success metrics to improve predictive precision and business outcomes
Translate model outputs into products and interfaces that Revenue teams and clients can act on; drive adoption and measure impact
Work with Client Analytics, Revenue, and data teams to ensure model compatibility with downstream systems and reporting
Evangelize ML best practices, run cross-functional alignment, and maintain strong stakeholder relationships