Principal - Data Scientist

Key responsibilities

• Define the personalization vision : Lead the evolution of JioHotstar's AI-native personalization platform, by designing systems that continuously understand every content we carry on the platform, who the customer is, what they intend to consume, and what they are most likely to value next, enabling seamless personalization across Search, Recommendations, Homepage, Ads, and Notifications.
• Architect next-generation AI systems : Build scalable, real-time personalization solutions using representation learning, foundation models, sequential user modeling, multimodal intelligence, semantic retrieval, and continuously learning systems.
• Solve personalization at scale : Drive innovation in customer understanding, intent prediction, cold-start, real-time recommendations, exploration vs. exploitation, diversity, and low-latency decision-making
• Build Platforms, Not Models : Develop foundational capabilities such as unified user and content representations, experimentation frameworks, feature platforms, and real-time inference services. Drive organizational thinking beyond optimizing isolated algorithms toward building continuously learning intelligence systems.
• Lead scientific excellence : Partner with Product, Engineering, Analytics, and Business leaders to define long-term AI strategy
• Develop Talent & Technical Excellence: Mentor senior data scientists, influence architectural decisions, champion AI-native ways of working, and establish scientific rigor across experimentation, measurement, and platform development

Skills and attributes for success

• Proven experience building and operating large-scale production personalization or search systems serving millions of users
• Demonstrated success translating scientific innovation into measurable customer and business outcomes
• Deep expertise in representation learning, behavioral embeddings, and sequential user modeling for personalization.
• Strong understanding of semantic retrieval, search, ranking, and recommendation systems at scale.
• Hands-on experience with Foundation Models, Transformers, LLMs, and multimodal AI .
• Knowledge of contextual bandits, reinforcement learning, causal inference, and long-term optimization techniques.
• Experience building real-time ML systems , including streaming pipelines, feature stores, vector retrieval, online inference, experimentation frameworks, and model serving.
• Strong engineering mindset with the ability to translate cutting-edge research into scalable, production-grade AI solutions.
• Excellent product intuition, with a focus on solving customer problems and delivering measurable business impact.
• Proven ability to thrive in ambiguous environments, solve complex problems from first principles, and influence cross-functional teams through technical leadership

Preferred education and experience

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