Warner Bros. Discovery is looking to develop and deploy machine learning solutions for consumer growth, including fraud detection, pricing optimization, and user behavior modeling, to drive business impact.
Requirements
- 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
- 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
Responsibilities
- Build complete ML pipelines from data processing to model deployment and monitoring in production environments
- Design and implement machine learning models for growth applications, from classical algorithms to deep learning approaches
- Work closely with product, engineering, and senior researchers to translate requirements into effective ML solutions
- Guide junior data scientists and contribute to team knowledge sharing
- Stay current with ML research and explore new methodologies relevant to consumer growth challenges
Other
- PhD/MS in Machine Learning, Data Science, or closely related field
- 3+ years (PhD) or 5+ years (MS) of hands-on machine learning experience
- Strong desire to learn new techniques and adapt to evolving business needs
- Ability to clearly articulate ML concepts to diverse stakeholders
- 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.
