Staff Data Scientist - Viewer experience
Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Jun 1, 2026. JioStar scores B on the Alion truth index.
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: The Viewer experience team focuses on revolutionizing content discovery across JioStar's platform. Our aim is to provide users with an intuitive and personalized experience, enabling seamless exploration and enrichment of their interests. Our data science team develops advanced algorithms that understand user preferences and content relationships to deliver relevant recommendations at scale.
Working alongside ML engineers, developers, designers, and content curators, we translate business challenges into algorithmic solutions that analyze user preferences and behaviors to deliver immersive content discovery experiences. Our work directly influences how millions of users discover content daily, making our team a critical driver of user engagement and business success. We embrace a culture of experimentation, rigorous evaluation, and continuous improvement to enhance our recommendation capabilities.
Key responsibilities:
Lead the vision and strategy for recommendation algorithms across the JioStar platform, identifying opportunities to enhance personalization and content discovery
Design and develop sophisticated recommendation models leveraging collaborative filtering, content-based techniques, deep learning, and hybrid approaches
Translate complex business requirements into data science solutions, driving alignment across product, engineering, and business stakeholders
Build evaluation frameworks and metrics that measure recommendation quality across dimensions including relevance, diversity, freshness, and business impact
Lead A/B testing and experimental design to validate algorithmic improvements and quantify business impact
Develop novel approaches to recommendation challenges including cold-start problems, exploration-exploitation tradeoffs, and multi-objective optimization
Collaborate closely with ML Engineering to ensure algorithms can be efficiently implemented at scale
Analyze user behavior patterns to identify segments and personalization opportunities
Provide mentorship to junior data scientists and establish best practices for the data science organization
Stay current with research in recommendation systems and personalization, bringing innovative approaches to our platform
Skills and attributes for success:
Deep expertise in recommendation system algorithms, including collaborative filtering, content-based, neural networks, and multi-stage approaches
Experience with candidate generation, ranking, and slate optimization for personalized user experiences
Strong background in reinforcement learning, bandits, and long-term reward modeling for recommendation systems
Experience with transformer architectures, LLMs, and their application to personalization
Knowledge of RLHF reward modeling/alignment techniques for improved recommendation systems
Hands-on experience with Python, SQL, and TensorFlow/PyTorch for implementing and evaluating algorithms
Knowledge of multi-task learning, transfer learning, and embedding techniques for users, items, and contexts
Understanding of content life cycles, seasonality, and timing's impact on recommendation strategies
Proven track record of developing recommendation systems that drive meaningful business outcomes
Experience with experimental design and A/B testing methodologies for recommendation algorithms
Ability to balance algorithmic exploration with user enjoyment in recommendation design
Strong leadership capabilities with demonstrated experience mentoring junior data scientists
Preferred education and experience:
Bachelor's in Computer Science, Statistics, Mathematics, or related quantitative field with 10+ years of experience in applied data science, including at least 5 years working specifically with recommendation systems.
Experience in streaming media, entertainment, or similar content platforms strongly preferred.
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.