Principal Data Scientist

The Principal Research Scientist (Recommender Systems) leads large and complex technical projects by developing innovative machine learning algorithms and directing ML and AI researchers and engineers towards scalable ML solutions for HBO Max. The role focuses on advancing personalisation, recommender systems and search to drive user experience and growth. The postholder partners closely with product, engineering, content, marketing and research stakeholders across WBD to identify ML opportunities, accelerate AI innovation and ensure delivery of impactful business solutions.

• Lead large and complex technical projects by developing innovative machine learning algorithms and directing ML and AI researchers and engineers towards scalable ML solutions for HBO Max.
• Develop innovative data science solutions that use machine learning and deep learning algorithms, statistical and quantitative modelling approaches to support product, engineering and marketing initiatives.
• Act as a hands-on leader to mentor the team in the latest machine learning approaches and introduce new technologies and processes.
• Partner with ML engineering leadership to design and develop scalable machine learning systems to accelerate the learning cycle.
• Identify data science opportunities that deliver business value.
• Formulate key areas of the ML/AI roadmap and educate internal and external stakeholders at all levels to drive implementation and measurement.
• Provide thought leadership to enable ML/AI applications.
• Develop and evangelise best practices for scoping, building, validating, deploying and monitoring ML/AI products.
• Prepare and present ML modelling results and analytical insights that help drive the business to senior leadership.

• Masters in Computer Science, Mathematics, Physics, Engineering, Statistics, Operations Research, or other equivalent quantitative fields.
• 8+ years of work experience in Machine Learning, AI and Data Science with a proven track record of driving innovation and business impacts.
• Strong experience in recommender systems, personalisation systems, collaborative filtering and information retrieval systems.
• Strong machine learning, deep learning and statistical modelling expertise, such as causal inference modelling, ensembles, neural networks, NLP, reinforcement learning and bandits.
• Familiarity and experience with modern large language model based techniques for recommender systems and personalisation.
• Advanced knowledge of SQL and experience with big data platforms (AWS, Snowflake, Spark, Google Cloud etc.).
• Proficiency in machine learning and deep learning languages and platforms (Python, TensorFlow, Keras, PyTorch etc.).
• Experience in deploying machine learning algorithms and advanced modelling solutions.
• Proven ability to deliver results in a fast-paced, high-energy environment.
• Strong communication skills and the ability to explain complex analysis and algorithms to a non-technical audience.
• Ability to work effectively in cross-functional teams to build trusted partnerships.

• PhD in a relevant quantitative field.
• Working experience in the digital media and entertainment industry.

• Actual salaries will vary based on a variety of job-related factors, including but not limited to geographic location, external market data, internal equity, skill set, experience, training, education, and/or performance.
• Base pay is just one component of the total compensation package.
• Other rewards may include annual bonuses, short- and long-term incentives, and programme-specific awards.

• Health insurance coverage.
• Employee wellness programme.
• Life and disability insurance.
• Retirement savings plan.
• Paid holidays, sick time and vacation.