Data Scientist II, Hyderabad

Welcome to Warner Bros. Discovery… the stuff dreams are made of.

Who We Are…

When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are thestorytellers bringing our characters to life, the creators bringing them to your living rooms and thedreamers creating what’s next…

From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.

Data Scientist II, Hyderabad 

About Warner Bros. Discovery: 

Warner Bros. Discovery is a premier global media and entertainment company with an iconic portfolio of content, brands, and franchises across television, film, streaming, sports, news, and gaming. We connect audiences around the world to the stories, experiences, and moments they love. 

For more information, please visitwww.wbd.com. 
  

Meet Our Team: 

Warner Bros. Discovery brings together iconic entertainment, news, sports, and digital brands including HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, and Food Network. Within the SPARK organization, our Hyderabad data science and machine learning teams transform first-party audience signals into capabilities that power identity, audience intelligence, advertising, personalization, forecasting, engagement, and retention. 

Our Data Scientists partner closely with Machine Learning Engineering, Product, Data Engineering, Ad Sales, and business teams to frame the right problems, build rigorous models and measurement approaches, and turn insight into measurable product and business impact. 

We work primarily with Databricks, Snowflake, and AWS, and we are early adopters of modern AI and agentic development workflows where they help us improve quality, speed, and repeatability. 

About the Role: 

As a Data Scientist, you will be a hands-on modeling and experimentation leader for WBD’s consumer platforms. You will translate complex product and business questions into measurable data science opportunities, build models and evaluation frameworks, and partner with Machine Learning Engineering to bring validated solutions into production. Your work will directly influence identity resolution, audience intelligence, personalization, retention, engagement, advertising effectiveness, and customer experience across WBD's global streaming platforms. 

What You’ll Do: 

• Data Science & Modeling: Build and improve models for probabilistic identity resolution, audience modeling, segmentation, content affinity, genre-preference modeling, forecasting, fraud and abuse detection, promo optimization, personalization, and lifecycle engagement. 

• Experimentation & Measurement: Design experiments, evaluation frameworks, baselines, success metrics, and promotion criteria that measure both model quality and business impact. 

• Production Partnership: Partner with Machine Learning Engineers to move validated models into scalable production pipelines with clear expectations for reproducibility, monitoring, drift detection, data quality, calibration, and long-term model health. 

• Business Problem Framing: Work with Product, Engineering, Data Science, Data Engineering, Ad Sales, and business stakeholders to turn ambiguous opportunities into well-scoped data science solutions. 

• Insight to Impact: Communicate findings, tradeoffs, risks, and recommendations clearly to technical and non-technical audiences. 

• Technical Quality: Help define reusable standards for feature and label quality, leakage prevention, model evaluation, documentation, experimentation rigor, and production readiness. 

What to Bring 

• 3–5 years of hands-on experience building data science, statistical modeling, or machine learning solutions for real-world products or business systems. 

• Strong ability to translate business problems into hypotheses, data science problem statements, success metrics, and actionable recommendations. 

• Deep practical knowledge of statistical modeling, machine learning fundamentals, causal inference, experimentation, forecasting, ranking, recommendation, calibration, and model evaluation. 

• Strong programming and analytical skills in Python and SQL; experience with Spark or large-scale distributed data processing is strongly preferred. 

• Hands-on experience with Databricks, Snowflake, AWS, MLflow, notebooks, experiment tracking, or similar data and ML tools. 

• Experience partnering with Machine Learning Engineering or platform teams to operationalize models, 

• Ability to collaborate effectively with Product, Engineering, Data Engineering, Machine Learning Engineering, Finance, Ad Sales, and business stakeholders in a global environment. 

• Excellent communication skills, including the ability to explain technical methods, model tradeoffs, uncertainty, and business implications to varied audiences. 

You’ll Be Successful If You 

• Enjoy turning ambiguous business problems into clear, measurable opportunities for data science and machine learning. 

• Care deeply about experimentation quality, model reliability, and real-world impact. 

• Communicate clearly with both technical and non-technical partners. 

• Influence technical direction through collaboration, evidence, and sound judgment. 

• Enjoy working across data science, engineering, product, and business teams to solve meaningful problems. 

Our Technology Stack: 

• Primary platforms: Databricks, AWS 

• Warehouse: Snowflake 

• Languages: Python, SQL; Scala as needed 

• ML and data tools: Spark, MLflow, notebooks, experiment tracking, model evaluation frameworks 

• Activation contexts: Personalization systems, Mosaic, FreeWheel, Google Ad Manager, and related audience activation platforms where applicable 

Preferred: 

• Master’s degree or Ph.D. in Computer Science, Statistics, Machine Learning, Data Science, Engineering, Mathematics, Economics, or a related quantitative field. 

• Experience in streaming, media, advertising technology, consumer identity, fraud, recommendations, personalization, forecasting, lifecycle engagement, or audience intelligence. 

• Experience with uplift modeling, causal impact analysis, lookalike modeling, clean-room or DCR analysis, graph-based methods, or multi-objective optimization. 

• Experience building reusable evaluation frameworks, model quality standards, or scalable data science patterns across teams. 

What We Offer: 

• A great place to work. 
• Equal opportunity employer. 

• Fast-track growth opportunities. 

How We Get Things Done…

This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them atwww.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.

Championing Inclusion at WBD

If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit ouraccessibility page for instructions to submit your request.