Product Manager (Feed)

What does the team do:

The SC Feed is the core of the ShareChat experience: it decides what millions of users across India see every time they open the app. We're looking for a Product Manager who can sit at the intersection of product and machine learning, and who wants to own how the feed gets smarter, more personal, and more engaging.

You'll work closely with Data Science, ML Engineering, and Analytics to shape the roadmap for personalisation and ML-driven feed optimisation, with a clear charter: improve user retention and time spent.

What you'll do:

• Own the product strategy and roadmap for the SC Feed, with a focus on personalisation and ranking improvements that move retention and time spent.
• Partner with Data Science and ML teams to identify modelling opportunities and translate them into product solutions that scale.
• Define success metrics for feed initiatives, design experiments, and run A/B tests from hypothesis to decision.
• Dig into user behaviour data yourself using SQL and Python to find problems worth solving and validate what's working.
• Write clear product requirements and drive execution across engineering, design, and data teams, keeping turnaround tight.
• Balance short-term experiment wins with longer-term bets on feed quality, content diversity, and user satisfaction.
• Communicate progress, trade-offs, and results to leadership and cross-functional stakeholders.

What we're looking for:

• 4-6 years of product management experience, ideally on consumer products at scale.
• Strong SQL skills and working proficiency in Python for analysis.
• A solid understanding of how recommendation systems and ML models work, enough to have productive conversations with data scientists about features, objectives, and model trade-offs.
• Experience running experiments and making decisions from data.
• Sharp product judgement and the ability to turn ambiguous problems into clear, prioritised plans.
• Clear written and verbal communication.

Good to have:

• Hands-on experience with feed, ranking, search, or recommendation products.
• Exposure to ML model evaluation, ranking metrics, or experimentation platforms.
• An engineering or quantitative background.
• Familiarity with user behaviour in Bharat and regional-language internet users.