Staff, Data Science & Applied AI

Warner Media, LLC.; Atlanta (GA); On-site; USD 140,000 - 190,000; Full time

Job summary

Warner Bros. Discovery is seeking a Staff, Data Science & Applied AI to advance analytics across Entertainment, Streaming, and Direct-to-Consumer platforms.

You will translate complex business challenges into scalable data products and production-grade models, partnering with product, engineering, and business stakeholders. Responsibilities include building ML/GenAI capabilities, designing CI/CD for model lifecycles, and ensuring governance and responsible AI practices across enterprise data

Qualifications

• Bachelor’s degree or higher in a quantitative field.
• 8+ years in data science; 2+ years GenAI.
• Proven production-grade AI/ML solutions with measurable business impact.

Responsibilities

• Design, develop, and deploy statistical, predictive, and ML models across domains.
• Collaborate with Data Engineering and DevOps to productionize ML and GenAI solutions.
• Develop reusable AI frameworks and automation to improve productivity across teams.

Skills

Applied data science

Statistical modeling

Machine learning engineering

Business impact

Stakeholder collaboration

Education

Bachelor’s degree in a quantitative field

MS or higher in a relevant field

Tools

Pinecone

Weaviate

OpenSearch

FAISS

RAG pipelines

Azure OpenAI

Job description

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 the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers 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.

Your New Role:

As Staff, Data Science & Applied AI, you will be a core technical contributor within the Enterprise Data & AI Solutions team supporting Warner Bros. Discovery’s global portfolio - including Studios, Streaming, Linear Networks, Consumer Products, Games, and Direct-to-Consumer platforms.

This role is designed for a hands-on expert in applied data science who thrives at the intersection of statistical rigor, machine learning engineering, and business impact. You will translate complex business challenges into scalable analytical solutions, production-grade models, and data products that drive measurable enterprise value.

You will operate as a senior individual contributor, partnering closely with Product, Engineering, and Business stakeholders to design, develop, deploy, and scale advanced analytics and AI capabilities across the organization.

Key Responsibilities include:

Advanced Analytics & Machine Learning

• Design, develop, and deploy statistical, predictive, and machine learning models across domains such as customer analytics, forecasting, personalization, optimization, and content performance.
• Apply advanced techniques including ensemble methods, gradient boosting, deep learning, NLP, time-series forecasting, and recommendation systems.
• Ensure model robustness through rigorous validation, monitoring, and performance tracking.

Generative AI & LLM Applications

• Design and implement Generative AI solutions leveraging large language models (LLMs) for use cases such as knowledge retrieval, content intelligence, metadata enrichment, summarization, and workflow automation.
• Develop and optimize prompt engineering strategies, evaluation frameworks, and guardrails to ensure high-quality, reliable outputs.
• Architect Retrieval-Augmented Generation (RAG) pipelines integrating structured and unstructured enterprise data sources.
• Fine-tune or adapt foundation models where appropriate using parameter-efficient techniques (e.g., LoRA, adapters) aligned with business needs.
• Implement evaluation pipelines to measure hallucination rates, bias, latency, cost efficiency, and model quality in production environments.
• Collaborate with Responsible AI and Governance teams to ensure compliance with enterprise AI policies, data privacy standards, and ethical AI practices.

Product Ionization & AI Engineering

• Collaborate with Data Engineering and DevOps teams to productionize ML and GenAI solutions in scalable cloud environments.
• Design CI/CD pipelines for model lifecycle management, including experimentation tracking, versioning, and automated retraining.
• Implement monitoring frameworks for model drift, prompt drift, performance degradation, and data integrity.

Automation & AI Framework Development

• Develop reusable ML and GenAI frameworks, accelerators, and internal utilities that improve productivity across teams.
• Advance automation initiatives to reduce manual workflows and enhance analytical velocity.
• Stay current with cutting-edge advancements in foundation models, multimodal AI, and agentic architectures to continuously elevate enterprise AI capabilities.

Qualifications & Experiences:

• Bachelor’s degree, MS, or greater in Computer/Data Science, Engineering, Mathematics, Statistics, or related quantitative discipline.
• 8+ years relevant experience in data science, 2+ experience in GenAI
• Demonstrated track record of delivering production-grade AI/ ML solutions with measurable business impact.

Generative AI & Large Language Model (LLM) Expertise

• Hands-on experience designing and deploying Generative AI solutions using large language models (e.g., GPT-class models, open-source foundation models, or enterprise LLM platforms).
• Strong proficiency in prompt engineering, structured output design, few-shot learning strategies, and systematic prompt optimization
• Experience building Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and enterprise data sources.
• Familiarity with embedding models, semantic search, and vector stores (e.g., Pinecone, Weaviate, OpenSearch, FAISS, or equivalent).
• Experience fine-tuning or adapting foundation models using parameter-efficient approaches (e.g., LoRA, adapters, instruction tuning).
• Understanding of LLM evaluation methodologies, including hallucination detection, bias assessment, response quality scoring, and cost-performance trade-offs.
• Exposure to multimodal AI (text, image, audio, video) and agent-based workflows is a plus.
• Experience working with enterprise AI platforms (e.g., AWS Bedrock, Azure OpenAI, Databricks Model Serving, Snowflake Cortex, or equivalent).
• Understanding of Responsible AI principles, data privacy considerations, and model governance requirements in regulated environments.

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 at www.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

Warner Bros. Discovery embraces 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, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by 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.