Staff Product Manager (Recommendations)

The Staff Product Manager (Recommendations) will shape JioHotstar’s content-discovery strategy for a platform serving more than 500 million users. The role owns recommendation surfaces users encounter when opening the app, including personalised, ML-powered, popularity-based and contextual content surfaces. Its goal is to improve recommendation quality, retention and engagement through data-informed product decisions and collaboration with ML and engineering teams.

Responsibilities

• Research recommendation quality, user engagement and content-discovery gaps; assess the return on personalisation investments.
• Turn user-behaviour signals, model performance and content-catalogue dynamics into clear product requirements and measurable improvements.
• Influence roadmaps across Recommendations and related Search, Watch Experience and Growth integrations. Work with ML Engineering, Data Science and Platform teams on priorities beyond the immediate recommendations domain.
• Adjust plans in response to content launches, live sports and seasonal shifts, communicating effects on recommendation quality. Own at least one KPI aligned with product objectives and key results.
• Build expertise in a functional area, contribute to hiring and mentor junior product managers.

Qualifications and attributes:

• Minimum 7 years of experience, including at least 5 years in product management and at least 2 years owning ML or recommendation products at consumer scale, with measurable metric improvements from shipped work.
• Fluency in the ML product lifecycle, including feature engineering, A/B experiment design, metric interpretation and launch readiness. Understand how recommendation models are trained, evaluated and deployed well enough to collaborate with and challenge technical partners.
• Ability to frame business and user problems as ML problems, distinguish data-quality, model-behaviour and product-definition issues, and connect algorithmic changes to outcomes. Strong communication, structured problem-solving, user empathy, experimentation, competitor benchmarking and cross-functional influence are sought.
• A bachelor’s or master’s degree, or equivalent, is preferred.

The position is based in Bengaluru, India, within the Recommendations & Personalisation team in JioHotstar’s Viewer Experience organisation.