Job Summary: Lead the development of sophisticated recommendation algorithms that power personalized content discovery across JioStar's platform, driving measurable improvements in user engagement, satisfaction, and retention through data-driven innovations.
About the team:
At JioHotstar, the Viewer Experience (VX) org is at the heart of how millions discover, engage with, and fall in love with our platform. We own the end-to-end user journey—from first app launch to daily habit loops—across Search, Personalization, Watch Experience, Interactivity, and more. We blend world-class engineering, ML, design, and data to deliver a seamless, personalized, and engaging OTT experience at massive scale. If you're passionate about building immersive, intelligent, and performant user experiences that delight a billion users, join us in shaping the future of streaming.
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Lead the vision and strategy across the JioStar platform, identifying opportunities to enhance personalization and content discovery
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Design and develop sophisticated recommendation models leveraging collaborative filtering, content-based techniques, deep learning, and hybrid approaches
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Translate complex business requirements into data science solutions, driving alignment across product, engineering, and business stakeholders
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Build evaluation frameworks and metrics that measure recommendation quality across dimensions including relevance, diversity, freshness, and business impact
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Lead A/B testing and experimental design to validate algorithmic improvements and quantify business impact
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Develop novel approaches to recommendation challenges including cold-start problems, exploration-exploitation tradeoffs, and multi-objective optimization
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Collaborate closely with ML Engineering to ensure algorithms can be efficiently implemented at scale
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Analyze user behavior patterns to identify segments and personalization opportunities
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Provide mentorship to junior data scientists and establish best practices for the data science organization
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Stay current with research in recommendation systems and personalization, bringing innovative approaches to our platform
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Deep expertise in recommendation system algorithms, including collaborative filtering, content-based, neural networks, and multi-stage approaches
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Experience with candidate generation, ranking, and slate optimization for personalized user experiences
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Strong background in reinforcement learning, bandits, and long-term reward modeling for recommendation systems
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Experience with transformer architectures, LLMs, and their application to personalization
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Knowledge of RLHF reward modeling/alignment techniques for improved recommendation systems
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Hands-on experience with Python, SQL, and TensorFlow/PyTorch for implementing and evaluating algorithms
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Knowledge of multi-task learning, transfer learning, and embedding techniques for users, items, and contexts
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Understanding of content life cycles, seasonality, and timing's impact on recommendation strategies
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Proven track record of developing recommendation systems that drive meaningful business outcomes
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Experience with experimental design and A/B testing methodologies for recommendation algorithms
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Ability to balance algorithmic exploration with user enjoyment in recommendation design
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Strong leadership capabilities with demonstrated experience mentoring junior data scientists
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Master's or PhD in Computer Science, Statistics, Mathematics, or related quantitative field with 7+ years of experience in applied data science.
About Us
Perched firmly at the nucleus of spellbinding content and innovative technology, JioStar is a leading global media & entertainment company that is reimagining the way audiences consume entertainment and sports. Its television network and streaming service together reach more than 750 million viewers every week, igniting the dreams and aspirations of hundreds of million people across geographies.
JioStar is an equal opportunity employer. The company values diversity and its mission is to create a workplace where everyone can bring their authentic selves to work. The company ensures that the work environment is free from any discrimination against persons with disabilities, gender, gender identity and any other characteristics or status that is legally protected.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
