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Urgent! Staff Data Scientist - Password Sharing Job Opening In San Francisco – Now Hiring Warner Bros Discovery

Staff Data Scientist Password Sharing



Job description

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

About the Role

We're seeking a Staff Data Scientist to develop and deploy machine learning solutions for consumer growth, including fraud detection, pricing optimization, and user behavior modeling.

You'll combine strong technical skills with a passion for learning to build scalable ML systems that drive business impact.

This role requires a blend of strong research skills, mathematical rigor, and production-grade engineering practices.

You will also act as a mentor to junior scientists, collaborate cross-functionally with product, engineering, and business stakeholders, and advance the company’s research agenda through thought leadership and, when possible, publications in top-tier venues.

Key Responsibilities

  • End-to-End Delivery: Build complete ML pipelines from data processing to model deployment and monitoring in production environments

  • ML Development: Design and implement machine learning models for growth applications, from classical algorithms to deep learning approaches

  • Cross-Functional Collaboration: Work closely with product, engineering, and senior researchers to translate requirements into effective ML solutions

  • Mentorship: Guide junior data scientists and contribute to team knowledge sharing

  • Research & Innovation: Stay current with ML research and explore new methodologies relevant to consumer growth challenges

  • Required Qualifications

  • Education: PhD/MS in Machine Learning, Data Science, or closely related field

  • Experience: 3+ years (PhD) or 5+ years (MS) of hands-on machine learning experience

  • Technical Skills

  • Proficient in Python and ML frameworks (PyTorch, TensorFlow, Scikit-learn, XGBoost)

  • Experience with SQL and large-scale data processing

  • Proven track record deploying ML models to production

  • Mindset: Strong desire to learn new techniques and adapt to evolving business needs

  • Communication: Ability to clearly articulate ML concepts to diverse stakeholders

  • Preferred Qualifications

  • Experience in consumer-facing applications (growth, fraud, personalization)

  • Familiarity with distributed computing systems (Spark, Ray)

  • Publications in ML conferences or contributions to open-source projects

  • 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 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.


    Required Skill Profession

    Mathematical Science Occupations



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