Principal Data Scientist

Storytelling is, and will always be, the heart of what we do at Skydance.

Our vision is to build a thriving entertainment ecosystem where stories and worlds are imagined, brought to life and experienced. We create for every age and audience, anchored by the strength of our content and experiences and the depth of our connection with fans. We are creator-first, audience-focused, tech-forward, globally scaled.

Here, you’ll work with talented teams that move fast, think boldly and collaborate with purpose to deliver results. We aim high, champion the best ideas and win together, earning the trust of our employees, creators, partners and audiences every day.

If you’re energized by the opportunity to help build the next-generation global media and entertainment company powered by creativity and technology, we’d be thrilled to welcome you aboard. LET’S GO!

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As a Principal Data Scientist, you will play a pivotal role in architecting, developing, and deploying high-impact machine learning and data science solutions across Warner Bros. Discovery’s global businesses. This role is ideal for a seasoned technical leader with 14–16 years of total experience, including 10–12 years of deep, hands-on experience in applied data science, machine learning, and statistical modeling. You will translate complex business problems into scalable analytical solutions—leveraging predictive modeling, optimization, experimentation, NLP, computer vision, and modern ML engineering practices. You will lead end-to-end development of ML models, champion scientific rigor, and ensure robust operationalization through modern MLOps practices. Experience in the Media & Entertainment sector—content, streaming, audience behavior, ad intelligence, or metadata systems—is a significant plus. This is a high-impact role requiring strong technical expertise, business acumen, problem-solving skills, and the ability to guide cross functional partners across Product, Engineering, Technology, and Business domains.

1. Core Data Science & Machine Learning Expertise

• Design, build, and scale advanced machine learning models across predictive analytics, NLP, CV, forecasting, optimization, and recommender systems.
• Apply strong statistical foundations—hypothesis testing, probability modeling, causal inference, and experiment design—to solve complex business problems.
• Develop interpretable and explainable ML models, ensuring scientific rigor, reproducibility, and operational robustness.
• Conduct feature engineering, model selection, hyperparameter tuning, and validation using modern ML frameworks.
• Translate ambiguous problems into structured analytic approaches with measurable impact.

2. ML Engineering & MLOps Execution

• Build production-grade ML pipelines integrating with WBD’s data ecosystem (Snowflake, AWS, GCP, Databricks).
• Implement CI/CD, model monitoring, drift detection, alerting, and model performance governance.
• Contribute to the design of feature stores, experimentation platforms, and ML observability frameworks.
• Work closely with data engineering and platform teams to ensure scalable, reliable model deployment.

3. Applied Data Science Delivery for High-Value Business Problems Lead delivery of ML solutions for domains such as:

• Content performance and ratings prediction
• Audience segmentation, churn and lifetime value modeling
• Search ranking, discovery, and personalization systems
• Metadata enrichment and content understanding using NLP & CV
• Operational forecasting and automation Convert analytical outcomes into actionable insights—delivering high-ROI recommendations to product and business stakeholders.

4. Stakeholder Partnership & Communication

• Partner with senior leaders across Streaming, Technology, Product, Content, and Marketing.
• Present complex modeling results clearly to non-technical audiences, influencing business decisions with data-driven insights.
• Shape and guide analytical roadmaps aligned to enterprise priorities.

5. Leadership, Collaboration & Mentoring

• Mentor data scientists and ML engineers, elevating scientific rigor and best practices across the team.
• Lead project teams in experimentation, modeling, evaluation, and productionization.
• Promote knowledge sharing, documentation standards, and internal communities of practice.
• Champion responsible AI, model governance, and ethical data usage across engagements.

Qualifications & Experiences:

• Master’s degree (or Ph.D. preferred) in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related fields.
• 14–16 years of total experience, with 10–12 years in Data Science, ML, and advanced analytics.
• Strong hands-on expertise in:
  • Predictive modeling, optimization, deep learning, NLP, and CV
  • Python, SQL, PyTorch/TensorFlow, Scikit-learn, ML frameworks
  • ML Ops, model deployment, monitoring, and observability
  • Statistical modeling, experiment design, Bayesian methods
  • Cloud platforms (AWS/GCP/Snowflake)
• Demonstrated track record of delivering business impact through ML solutions in large-scale environments.
• Strong communication skills with demonstrable ability to influence cross-functional teams.

Preferred:

• Experience in Media & Entertainment, streaming, digital advertising, metadata, or audience intelligence.
• Hands-on exposure to foundation models, LLMs, embeddings, or generative AI.
• Experience with video intelligence, OCR/CV pipelines, or content metadata engines.
• Publications, patents, or conference-level contributions in ML/AI.

About Skydance

Skydance is a next-generation global media and entertainment company, comprised of three business segments: Studios, Direct-to-Consumer, and TV Media. Skydance's portfolio unites legendary brands, including Paramount, Warner Bros., HBO and HBO Max, Paramount+, Pluto TV, CBS, CNN, CBS Sports, TNT Sports, Nickelodeon, Cartoon Network, MTV, Food Network, BET, HGTV, and Comedy Central.

Some Important Details

We embrace the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit. In line with the laws of the country or region in which the role is based, this includes consideration without regard to race, color, ethnicity, national origin, citizenship status, religion or belief, sex, gender, gender identity or expression, sexual orientation, age, marital status, pregnancy, parenthood, physical or mental disability, genetic information, military or protected veteran status, union status or any other category protected by applicable law.

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 our accessibility page for instructions to submit your request.