As a Data Scientist II, you will build and optimize end-to-end personalization systems, refining scoring, ranking, and eligibility models; the role emphasizes robust experimentation, model monitoring, and alignment with lifecycle-based objectives, leveraging advanced ML and data insights to address cold starts, data drift, and explainable outcomes.

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.

Key responsibilities :

- Analyze large-scale user behavior and content metadata to uncover actionable insights and build impactful personalization models.

- Design, develop, and deploy ML models including collaborative filtering, content-based recommendations, sequence models, and retrieval-ranking pipelines.

- Integrate models into production systems ensuring low-latency, high-accuracy performance at scale.

- Collaborate with engineers, product managers, designers, and data scientists to define personalization goals and drive feature impact across user journeys.

- Develop robust A/B test frameworks, analyze experiments, and drive iteration based on performance and user engagement.

- Actively monitor model performance, detect data drift, and refine strategies to improve long-term personalization quality.

- Leverage LLMs and embeddings to improve personalization for underrepresented content, new users, and diverse formats.

- Present technical strategies and results to cross-functional stakeholders and leadership.

Skills and attributes for success :

- Proven experience in data science and machine learning.

- Strong proficiency in Python, SQL, and relevant data science libraries (Pandas, Scikit-learn, TensorFlow, PyTorch, etc.

- Expertise in building and deploying machine learning models into production systems.

- Experience with big data technologies (e.g Hadoop, Spark) and cloud platforms (e.g , AWS, Google Cloud).

- Deep understanding of statistical analysis, machine learning, data mining, and predictive modeling techniques.

- Should be comfortable leveraging LLMs and internals.

- Strong problem-solving skills with the ability to translate business problems into data science solutions.

Preferred education and experience :

- Bachelors/Master's in Computer Science, Statistics, Mathematics, or related quantitative field with 2-4 years of experience in data science/machine learning.