Job Description
Responsibilities
Our Direct-to-Consumer (DTC) portfolio is a powerhouse collection of consumer-first brands, supported by media industry leaders, Comcast, NBCUniversal and Sky. When you join our team, you'll work across our dynamic portfolio including Peacock, NOW, Fandango, SkyShowtime, Showmax, and TV Everywhere, powering streaming across more than 70 countries globally. And the evolution doesn't stop there. With unequalled scale, our teams make the most out of every opportunity to collaborate and learn from one another. We're always looking for ways to innovate faster, accelerate our growth and consistently offer the very best in consumer experience. But most of all, we're backed by a culture of respect. We embrace authenticity and inspire people to thrive.
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.
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 the 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.
Salary Range: $145,000 - $175,000
Qualifications
• Advanced (Master or PhD) degree with specialization in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research or another quantitative field or equivalent.
• 4+ years of combined experience in advanced analytics 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, particularly in the areas different form the computer vision.
• 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.
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
• Knowledge of enterprise-level digital analytics platforms (e.g., Adobe Analytics, Google Analytics, etc.)
• 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
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. NBCUniversal will consider for employment qualified applicants with criminal histories in a manner consistent with relevant legal requirements, including the City of Los Angeles Fair Chance Initiative For Hiring Ordinance, where applicable.
If you are a qualified individual with a disability or a disabled veteran, you have the right to request a reasonable accommodation if you are unable or limited in your ability to use or access nbcunicareers.com as a result of your disability. You can request reasonable accommodations in the US by calling 1-818-777-4107 and in the UK by calling +44 2036185726.
Remote Exceptions: This position can be designated as fully remote or hybrid, meaning that the position is expected to contribute from either a non-NBCUniversal worksite, or most commonly an employee's residence.
Jobcode: Reference SBJ-rz85b7-18-227-111-48-42 in your application.