Staff Data Science & Applied AI

Warner Bros. Discovery

Confirmed live yesterday High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Atlanta, GA
Employment: Full-time
Posted: 6 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $222k

$151k $298k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $195,000–$249,000.

Based on 240 similar postings.

Employer

About Warner Bros. Discovery

Warner Bros. Discovery is a global media and entertainment company operating a broad portfolio of iconic content and brands including Warner Bros. film studio, HBO, CNN, Discovery Channel, and Max streaming service. Industry: Media & Entertainment

Warner Bros. Discovery currently has 58 open roles on FindRole.

Listed pay typically runs $132,300–$245,700 across 24 roles with salary data.

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At a glance

TL;DR · Staff Data Science & Applied AI

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As Staff, Data Science & Applied AI, you will join the Enterprise Data & AI Solutions team to support a global portfolio including Studios, Streaming, and Games. You will serve as a senior individual contributor, translating complex business challenges into scalable analytical solutions and production-grade models. Your daily work involves designing and deploying statistical, predictive, and machine learning models for customer analytics, forecasting, and personalization. You will build Generative AI solutions using large language models, developing prompt engineering strategies, evaluation frameworks, and Retrieval-Augmented Generation pipelines. Key technologies include deep learning, NLP, time-series forecasting, and vector databases like Pinecone or FAISS. You will also productionize solutions in cloud environments using CI/CD pipelines, ensuring model robustness through monitoring for drift, bias, and latency while adhering to Responsible AI principles.

Skills

Generative AI LLMs RAG Machine Learning NLP Deep Learning Prompt Engineering Fine-tuning LoRA Vector Databases Pinecone Weaviate OpenSearch FAISS AWS Bedrock Azure OpenAI Databricks Snowflake Cortex CI/CD Time-series Forecasting Recommendation Systems Gradient Boosting

What you'll do

Develop and deploy predictive and machine learning models for customer analytics, forecasting, and content performance.
Design and implement Generative AI solutions using large language models for knowledge retrieval and workflow automation.
Architect Retrieval-Augmented Generation (RAG) pipelines integrating structured and unstructured enterprise data sources.
Fine-tune foundation models using parameter-efficient techniques like LoRA to align with specific business needs.
Build CI/CD pipelines for model lifecycle management, including experimentation tracking, versioning, and automated retraining.
Create reusable ML and GenAI frameworks and internal utilities to improve productivity across the organization.
Implement monitoring frameworks to track model drift, prompt drift, and data integrity in production environments.
Ensure all AI solutions comply with enterprise data privacy standards and ethical AI governance policies.

What we're looking for

Bachelor’s degree, MS, or greater in Computer/Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline.
8+ years of relevant experience in data science.
Experience in Generative AI.
Demonstrated track record of delivering production-grade AI/ML solutions with measurable business impact.
Hands-on experience designing and deploying Generative AI solutions using large language models and prompt engineering.
Experience building Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and enterprise data sources.
Experience fine-tuning or adapting foundation models using parameter-efficient approaches like LoRA or adapters.
Exposure to multimodal AI and agent-based workflows (preferred).

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