Principal Data Scientist

Warner Bros. Entertainment Inc.$227K — $423K *
Consumer Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Master's in Computer Science, Mathematics, Physics, Engineering, Statistics, Operations Research, or equivalent quantitative field; PhD preferred
  • 8+ years of experience in Machine Learning, AI, and Data Science with a focus on driving innovation
  • Strong background in recommender systems, personalization systems, and collaborative filtering
  • Expertise in machine learning, deep learning, and statistical modeling techniques
  • Familiarity with large language models for recommender systems and personalization
  • Advanced SQL knowledge and experience with big data platforms like AWS and Google Cloud
  • Proficient in Python and machine learning frameworks such as TensorFlow and PyTorch

Responsibilities

  • Develop innovative data science solutions using machine learning and deep learning algorithms
  • Mentor team members in advanced machine learning techniques and introduce new technologies
  • Collaborate with ML engineering to create scalable machine learning systems
  • Identify and leverage data science opportunities to enhance business value
  • Establish key areas on the ML/AI roadmap and educate stakeholders on implementation
  • Provide thought leadership for ML/AI applications and methodologies
  • Present modeling results and analytical insights to senior leadership

Benefits

  • Collaborative work environment with cross-functional teams
  • Opportunities for continuous learning and professional development
  • Engagement in projects that directly impact user experience
  • Ability to influence direction in ML/AI solutions
  • Potential to work on large-scale, high-impact projects in digital media and entertainment
Full Job Description
Principal Research Scientist (Recommender Systems)

The Job

The Principal Research Scientist (Recommender systems) will lead large and complex technical projects by developing innovative machine learning algorithms and directing the work of talented Machine Learning (ML) and Artificial Intelligence (AI) researchers and engineers towards building scalable ML solutions for HBO Max. This role will be focused on advancing personalization and recommender systems and search to drive user experience and growth.

The person in the role will partner closely with product, engineering, content, marketing, and research stakeholders across WBD to identify ML opportunities, accelerate AI innovation, and to ensure delivery of impactful solutions for the business.

The Daily
  • Develop innovative data science solutions that utilize machine learning and deep learning algorithms, statistical and quantitative modeling approaches to support product, engineering and marketing initiatives.
  • Be a hands-on leader to mentor the team in the latest machine learning approaches, and to introduce new technologies and processes.
  • Partner with ML engineering leadership to design and develop scalable machine learning systems to accelerate the learning cycle.
  • Identify data science opportunities that deliver business value.
  • Formulate key areas of the ML/AI roadmap, and educate both internal and external stakeholders at all levels to drive implementation and measurement.
  • Provide thought leadership to enable ML/AI applications.
  • Develop and evangelize best practices for scoping, building, validating, deploying, and monitoring ML/AI products.
  • Prepare and present ML modeling results and analytical insights that help drive the business to senior leadership.


The Essentials
  • Masters in Computer Science, Mathematics, Physics, Engineering, Statistics, Operations Research, or other equivalent quantitative fields (PhD preferred)
  • 8 + years of work experience in Machine Learning, AI and Data Science with a proven track record to drive innovation and business impacts
  • Strong experience in Recommender systems, personalization systems, collaborative filtering and information retrieval systems.
  • Strong machine learning, deep learning, and statistical modeling expertise, such as causal inference modeling, ensembles, neural networks, NLP, reinforcement learning and bandits
  • Familiarity and experience with modern large language model based techniques for recommender systems and personalization.
  • Advanced knowledge of SQL and experience with big data platform (AWS, Snowflake, Spark, Google Cloud etc.)
  • Proficiency in machine learning and deep learning languages and platforms (Python, TensorFlow, Keras, PyTorch etc.)
  • Experience in deploying machine learning algorithms and advanced modeling solutions
  • Proven ability to deliver results in a fast-paced, high-energy environment
  • Strong communication skills and the ability to explain complex analysis and algorithms to non-technical audience
  • Works effectively cross functional teams to build trusted partnership
  • Working experience in digital media and entertainment industry preferred


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.

About Warner Bros. Entertainment Inc.

Warner Bros. Interactive Entertainment is an American video game publisher based in Burbank, California, and part of the newly-formed Global Streaming and Interactive Entertainment unit of Warner Bros. Discovery. WBIE was founded on January 14, 2004 under Warner Bros. and transferred to the Home Entertainment division when that company was formed in October 2005. WBIE manages the wholly owned game development studios TT Games, Rocksteady Studios, NetherRealm Studios, Monolith Productions, WB Games Boston, Avalanche Software, and WB Games Montréal, among others.
Learn more about Warner Bros. Entertainment Inc.
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Founded
1918

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