Sr. Principal Data Scientist (Agentic AI)
Who We Are…
Your New Role
1. Enterprise-Grade Applied AI & ML Leadership (IC)
- Act as one of WBD's
most senior technical ICs
in Data Science and Machine Learning.
- Lead the
end-to-end design and implementation
of advanced ML systems across: • Content intelligence & metadata enrichment
- Audience modelling & personalization
- Forecasting, optimization, and experimentation
- Advertising intelligence & monetization analytics
- Set
technical direction and standards
2. Advanced Modelling & Scientific Excellence
- Design and implement
state-of-the-art models
, including: • Large-scale recommender systems
- Time-series forecasting & probabilistic models
- Causal inference, experimentation & uplift modelling
- NLP, generative AI & multimodal ML systems
- Computer vision & video intelligence pipelines
- Apply rigorous statistical thinking, experimentation discipline, and scientific validation to all solutions.
- Serve as a
final technical reviewer
3. Architecture of Scalable ML Systems
- Architect
production-grade ML systems
integrated with WBD's cloud data ecosystem (AWS, Snowflake, GCP).
- Define best practices for: • Feature engineering & feature stores
- Model lifecycle management & MLOps
- CI/CD for ML, model monitoring, and drift detection
- Reproducibility, governance, and responsible AI
- Partner deeply with data engineering, platform, and product engineering teams to ensure scalable, resilient delivery.
4. High-Impact Business Problem Solving
- Own and deliver
mission-critical AI solutions
across: • Content performance prediction & ratings intelligence
- Marketing attribution & lifecycle analytics
- Search, discovery & ranking systems
- Ad load optimization & pricing intelligence
- Operational forecasting & automation
- Translate complex modelling outputs into
clear, executive-ready insights
5. Executive & Cross-Functional Influence (Without Line Management)
- Serve as a
trusted technical advisor
to senior leaders across Streaming, Content, Ad Sales, Marketing, and Technology.
- Communicate complex ML concepts with clarity and credibility to non-technical stakeholders.
- Influence enterprise AI roadmaps, architectural decisions, and investment priorities through expertise - not hierarchy.
6. Technical Mentorship & Community Leadership
- Mentor senior and staff-level data scientists through
technical guidance, design reviews, and deep problem-solving
.
- Contribute to internal AI communities of practice, technical forums, and standards bodies.
- Elevate overall engineering and scientific rigor across the Data Science organization.
Qualifications & Experiences
Master’s or Ph.D.
18–20 years
13–15 years
in Data Science/ML, including hands-on technical leadership.
- Deep expertise in: • Predictive modeling, optimization, and advanced ML techniques
- MLOps and large-scale model deployment
- Modern cloud ecosystems (AWS/GCP/Snowflake)
- Python, PyTorch, TensorFlow, SQL, ML frameworks
- Experiment design, causal inference, and statistical modeling
- Demonstrated experience in Media & Entertainment, streaming, digital advertising, or consumer intelligence.
- Strong track record of delivering enterprise-impact through AI solutions.
- Exceptional communication skills, including the ability to influence executives and inspire technical teams.
Preferred
- Experience developing or customizing Large Language Models or multimodal foundation models.
- Patent, publication, or conference-track record in ML/AI.
- Experience with video intelligence, CV for media workflows, or content metadata systems.
- Experience partnering with product and engineering organizations in a fast-paced environment.
How We Get Things Done…
Championing Inclusion at WBD
Not included in the source posting: what you'll do, benefits.
Skills
Who can apply
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