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Lead Data Engineer - ML & Data Platform InnovationThe Walt Disney Company • San Francisco, California, United States
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Lead Data Engineer - ML & Data Platform Innovation

The Walt Disney Company
  • US
    San Francisco, California, United States
  • US
    San Francisco, California, United States
Jetzt Bewerben

Über

On any given day at Disney Entertainment & ESPN Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming Disney’s media business for the future. Whether that’s evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney’s unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world. A few reasons why we think you’d love working for Disney Entertainment & ESPN Technology Building the future of Disney’s media business: DE&E Technologists are designing and building the infrastructure that will power Disney’s media, advertising, and distribution businesses for years to come. Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more. Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news. The Product & Data Engineering team is responsible for end to end development for Disney’s world-class consumer-facing products, including streaming platforms Disney+, Hulu, and ESPN+, and digital products & experiences across ESPN, Marvel, Disney Studios, NatGeo, and ABC News. The team drives innovation at scale for millions of consumers around the world across Apple, Android, Smart TVs, game consoles, and the web, with our platforms powering core experiences like personalization, search, messaging and data. Job Summary As a Lead Data Engineer in the Data Platforms team, you will be partnering closely with the Engineering, Architecture, and Product teams to lead development for prediction and optimization engines for our data platforms. The right person for this role should be experienced in crafting implementation for either machine learning technologies or data-driven algorithms. If you are someone who is proactive, inquisitive, and innovative, this is a phenomenal role for you! Responsibilities Drive ground-breaking innovation and apply state of the art machine learning statistics and insights in a variety of areas to boost Hulu and Disney in every aspect of data platforms, including engagement forecasting and performance metrics Invent and iterate novel solutions to challenging platform related problems in fast turn around Develop scalable and efficient methods for large scale data analysis and model development. Build and experiment brand new algorithms and models e2e throughout production rollout and continuous optimization. Collaborate with engineering teams, program managers, and product managers in an open, and creative environment. Mentor team members, and guide their technical development Basic Qualifications Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience Minimum of 7 years of working experience on large scale machine learning systems and statistics in leading internet companies. Solid understanding of ML technologies, mathematics and statistics. Proficient with Java, Python, Scala, large scale ML/DL platforms and processing tech stack. Passion for technology, open to interdisciplinary work and experience in building data-driven services and applications. Proven track record of thriving in a fast-paced, data-driven, collaborative environment is required. Preferred Qualifications Master's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience Experience with feature store and MLOps Experience with Tensorflow, Kubeflow or Sagemaker DISNEYTECH The hiring range for this position in Santa Monica & Glendale, CA and Bristol, CT is $149,300 to $200,200 per year, New York, NY & Seattle, WA is $156,300 to $209,600 per year, and in San Francisco, CA is $163,500 to $219,200 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered. About Disney Direct to Consumer: Disney’s Direct to Consumer team oversees the Hulu and Disney+ streaming businesses within Disney Entertainment helping to bring The Walt Disney Company’s best-in-class storytelling to fans and families everywhere. About The Walt Disney Company: The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise with the following business segments: Disney Entertainment, ESPN, Disney Parks, and Experiences and Products. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney’s stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished. This position is with Hulu, LLC, which is part of a business we call Disney Direct to Consumer.
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  • San Francisco, California, United States

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