AI-Driven Line & Buy Planning Product Lead

About the Role

Senior Product Manager, Line Planning & Buy Planning Decision Logic is responsible for making Gap Inc.'s line planning and buy planning applications intelligent. This role sits at the intersection of data science, product delivery, and merchandising – owning how predictive models are shaped, operationalized, and embedded into the workflows that Merchants, Buyers, and Planners rely on every day to build lines and commit to buys.

This is not a role for a PM who hands off to data science and waits. You will be a deep collaborator and co‑developer – fluent in how demand forecasting, assortment optimization, buy quantity, and attribute‑based line building models work, where they are in their maturity, and what it takes to translate partially‑built modeling capability into trustworthy, usable product. You will own how model outputs surface in the application, how users understand and act on recommendations, and how the system learns from override behavior and feedback.

You will serve as the connective tissue between Data Science, Engineering, and the business – ensuring that the intelligence built into the platform is accurate, explainable, and adopted.

• Own the product strategy for embedding data science models – including demand forecasting, assortment optimization, buy quantity recommendations, and attribute‑based line building – directly into Line Planning and Buy Planning application workflows.
• Partner deeply with Data Science to shape model requirements, define input/output specifications, and drive model development priorities as capabilities move from partial build to production.
• Define how model outputs are surfaced in the UI: inline recommendations, confidence indicators, explainability layers, and override mechanisms that keep users in control while building trust over time.
• Establish feedback loops between user behavior (overrides, edits, adoption rates) and model improvement – ensuring the application gets smarter with use.
• Maintain expert‑level understanding of each model in scope: how it works, where it performs well, where it fails, and what business conditions affect its reliability.

• Define and prioritize the backlog across model integration, UX, and workflow features – balancing user adoption needs with data science delivery timelines and engineering capacity.
• Write precise user stories, model contracts, and acceptance criteria that hold up across data science, engineering, and business stakeholder reviews.
• Lead UAT in partnership with Merchandising and Buying, designing test scenarios that validate recommendation accuracy, model explainability, and real‑world usability under seasonal planning conditions.
• Ensure production readiness for all model‑driven features – including monitoring, QA protocols, and incident response for model degradation or output failures.

• Serve as the primary product interface for Merchants, Buyers, and Planners – translating workflow needs into precise model and application requirements, and building confidence in AI‑driven recommendations through rigorous delivery and transparent communication.
• Communicate model confidence levels, known limitations, and data dependencies clearly – helping business partners calibrate when and how to rely on platform intelligence.
• Drive adoption of new intelligent capabilities through training, embedded support, and change management during go‑live periods.
• Represent Line Planning and Buy Planning Decision Logic in cross‑functional forums, ensuring roadmap dependencies with Data Science, Data Engineering, and adjacent P2M capabilities are visible and managed.

• 8–12+ years of experience in product management, with meaningful depth in data‑intensive or AI/ML product environments – ideally in retail, merchandising, or a related planning domain.
• Demonstrable experience owning products that embed machine learning or data science models into user‑facing workflows – not just integrating outputs, but shaping how models are built, validated, and trusted by end users.
• Deep fluency partnering with Data Science…