Staff Data Scientist, Content
HBO Max
Los Angeles, CAThis was removed by the employer on 6/21/2021 5:47:00 PM PST
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Full Time Job
LA, NY, or Seattle
The Job
As a Staff Data Scientist you will be a part of the Content Data Science team responsible for the day to day output for WarnerMedia's streaming service.
As a Staff Data Scientist, you will be responsible for using your expertise in advanced analytics and predictive modeling to guide your domain areas to solve business challenges and enable our organization to make data-driven decisions. In addition, you will design and build end-to-end data science solutions within a cloud-based analytics infrastructure, transforming the insights into actionable endpoints, carrying the data science solution to production, managing the publication of the endpoints for downstream consumption, and communicating the results to stakeholders across all levels.
The Daily
• Lead development of engagement forecasting across SVOD, AVOD and international, and content/ad valuation models to drive HBO Max content decision-making.
• Develop and build innovative data science solutions that utilize machine learning algorithms, statistical and quantitative modeling approaches to support content creation, acquisition, marketing, and distribution strategies and initiatives.
• Partner with content analytics and engineering teams to develop tools and foundational data sets for consumption from technical and non-technical stakeholders
• Develop cross-functional roadmaps, and educate both internal and external stakeholders at all levels to drive implementation and measurement.
• Be a hands-on thought leader and mentor senior and junior members on the team, and disseminate the latest machine learning approaches, and new techniques and processes across the data science organization.
• Manage project priorities and ensure timely delivery. Develop and evangelize best practices for scoping, building, validating, deploying, and monitoring data science models.
• Prepare and present data science results and analytical insights to stakeholders and leadership.
The Essentials
• Graduate degree in Computer Science, Mathematics, Physics, Engineering, Statistics, Operations Research, or other equivalent quantitative fields (Ph.D. 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 machine learning, deep learning, temporal forecasting, and statistical modeling expertise, such as causal inference modeling, ensembles, neural networks, reinforcement learning, NLP, and computer vision
• Proficiency in machine learning and deep learning languages and platforms (Python, R, TensorFlow, Keras, PyTorch, MXNet, LSTMs, Prophet, etc.)
• Advanced knowledge of SQL and experience with big data platforms (AWS, Snowflake, Spark, Google Cloud etc.)
• Self-starter and self-motivated with the proven ability to deliver results in a fast-paced, high-energy environment
• Works well in greenfield areas and is not afraid of ambiguity
• Deep knowledge of software engineering best practices including version control, testing, and deployment pipelines (CI/CD) in the context of machine learning
• Advanced experience on database development, management and ETL on big data platforms
• Strong communication skills and the ability to explain complex analysis and algorithms to a non-technical audience
• Knowledge of dashboarding (Tableau, Looker, etc.) or of equivalent report building experience
• Works effectively with cross functional teams to build trusted partnerships
• Working experience in digital media and entertainment industry is a bonus
Warner Media, LLC and its subsidiaries are equal opportunity employers. Qualified candidates will receive consideration for employment 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.