Staff Data Scientist - Viewer Experience

Job Summary

The incumbent 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.

General Information About The Company

Perched firmly at the nucleus of spellbinding content and innovative technology, it 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.

About The Team

At the project, 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.

Your 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

• Bachelors/Masters in Data Science, Statistics, Computer Science, Mathematics, or a related field with 8-10 years of experience in data science.
• Proven experience in data science and machine learning, preferably in personalization or recommendation systems.
• 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.
• Excellent verbal and written communication skills, with the ability to present complex information to non-technical stakeholders.