NBCUniversal Lead Data Scientist \\\| SmartRecruiters Google Chrome Microsoft Edge Apple Safari Mozilla Firefox . Lead Data Scientist Full-time Business Segment: Media Group Functions Company Description NBCUniversal is one of the world's leading media and entertainment companies. We create world-class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our global theme park destinations, consumer products, and experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, NBC Sports, Telemundo, NBC Local Stations, Bravo, and Peacock, our premium ad-supported streaming service. We produce and distribute premier filmed entertainment and programming through our powerhouse film and television studios, including Universal Pictures, DreamWorks Animation, and Focus Features, and the four global television studios under the Universal Studio Group banner, and operate industry-leading theme parks and experiences around the world through Universal Destinations & Experiences, including Universal Orlando Resort, home to Universal Epic Universe, and Universal Studios Hollywood. NBCUniversal is a subsidiary of Comcast Corporation. Visit www.nbcuniversal.com for more information. Our impact is rooted in improving the communities where our employees, customers, and audiences live and work. We have a rich tradition of giving back and ensuring our employees have the opportunity to serve their communities. We champion an inclusive culture and strive to attract and develop a talented workforce to create and deliver a wide range of content reflecting our world. Job Description Position Overview: As part of the Peacock Data Science team, the Lead Data Scientist will be responsible for creating recommendation and personalization solutions for one or more verticals of Peacock Video Streaming Service. Youll collaborate with an international, cross-functional team of engineers, architects, product managers and analysts to identify and prioritize enhancements to Peacocks personalization models. Your responsibilities will touch everything from feature creation to model evaluation and deployment, and youll have opportunities to work on cutting edge machine learning like foundation models and reinforcement learning. Responsibilities include, but are not limited to: Work with a group of data scientists in the development of recommendation and personalization models using statistical, machine learning and data mining methodologies. Drive the collection and manipulation of new data and the refinement of existing data sources. Translate complex problems and solutions to all levels of the organization. Collaborate with software and data architects in building real-time and automated batch implementations of data science solutions and integrating them into the streaming service architecture. Drive innovation of the statistical and machine learning methodologies and tools used by the team. Qualifications Qualifications/Requirements: Advanced (Master or PhD) degree with specialization in Statistics, Computer Science, Data Science, Machine Learning, Mathematics, Operations Research or another quantitative field or equivalent. 5+ years of combined experience in machine learning in industry or research. Experience with commercial recommender systems or a lead role in an advanced research recommender system project. Working experience with deep learning and graph methodologies in machine learning. Strong experience with deep learning using TensorFlow. Experience implementing scalable, distributed, and highly available systems using Google Could Platform. Experience with Google AI Platform/Vertex AI, Kubeflow and Airflow. Proficient in Python. Java or Scala is a plus. Experience in data processing using SQL and PySpark. Experience working with foundation models and other GenAI technologies. Desired Characteristics: Experience in media analytics and application of data science to the content streaming and TV industry. Good understanding of reinforcement learning algorithms. Experience with multi-billion record datasets and leading projects that span the disciplines of data science and data engineering. Experience with large-scale video assets Team oriented and collaborative approach with a demonstrated aptitude and willingness to learn new methods and tools. Additional Information As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision. NBCUniversal's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to . Job Location Google Maps requires functional cookies to be enabled I'm interested I'm interested I'm interested share this job Share on LinkedIn Share on Facebook Share on Twitter Share via email Share on Xing Share on WeChat Share to WeChat × Copy the link and open WeChat to share. Copy to clipboard Open WeChat Share to WeChat × Use Scan QR Code in WeChat and click ··· to share. Lead Data Scientist 1 Grant Way, Brentford, United Kingdom Full-time I'm interested I'm interested

The role requires an advanced degree (Master's or PhD) in a quantitative field such as Statistics, Computer Science, Data Science, Machine Learning, Mathematics, or Operations Research, or an equivalent. Candidates must possess at least five years of combined industry or research experience in machine learning. Experience with commercial recommender systems or a lead role in an advanced research recommender system project is necessary. Proficiency in deep learning, graph methodologies, and TensorFlow is required, along with experience implementing scalable systems on Google Cloud Platform. Experience with Google AI Platform/Vertex AI, Kubeflow, and Airflow, as well as proficiency in Python and data processing using SQL and PySpark, are also essential. Experience with foundation models and GenAI technologies is required.