Sr. Lead Data Scientist

Company Description

NBCUniversal owns and operates over 20 different businesses across 30 countries including a valuable portfolio of news and entertainment television networks, a premier motion picture company, significant television production operations, a leading television stations group, world-renowned theme parks and a premium ad-supported streaming service. Here you can be your authentic self. As a company uniquely positioned to educate, entertain and empower through our platforms, Comcast NBCUniversal stands for including everyone. We strive to foster a diverse and inclusive culture where our employees feel supported, embraced and heard. We believe that our workforce should represent the communities we live in, so that together, we can continue to create and deliver content that reflects the current and ever-changing face of the world. Click here to learn more about Comcast NBCUniversal’s commitment and how we are making an impact.

Job Description

Welcome to Peacock, the dynamic new streaming service from NBCUniversal. Here you’ll find more than a job. You’ll find a fast-paced, high-performance team of incredible colleagues that want to be at the epicenter of technology, sports, news, tv, movies and more. We work hard to connect people to what they love, each other and the world around them by creating shared experiences through culture-defining entertainment. 

As a company, we embrace the power of difference. Our team is committed to creating an organization that champions diversity and inclusivity for all by curating content and a workforce that represents the world around us.  We continue to challenge ourselves and the industry by being customer-centric, data-driven creatures of innovation. At Peacock, we are determined to forge the next frontier of streaming through creativity, teamwork, and talent. 

As a Sr. Lead Data Scientist on the Direct-to-Consumer Decision Sciences team, you will be responsible for designing and implementing advanced machine learning algorithms for algorithmic targeting solutions across the app, including promotion pricing. You will lead the development and deployment of machine learning solutions at scale to optimize the use of Peacock's first-party data to personalize the user experience and the app's dynamic surfaces, ultimately lifting enterprise metrics.

In this role, you will work closely with product teams to identify opportunities for targeting solutions and lead experiments to gather required data. You will research and validate machine learning solutions and work to build a robust and reusable targeting platform to ensure that solutions are tested and reliable. As a team expert and leader in advanced statistical and machine learning methodologies, you will guide both data scientists and projects to create machine learning solutions for multiple business verticals.

The responsibilities of this role range from working with product teams to determine when and where targeting solutions should be applied, leading experiments to gather required data, researching and validating a machine learning solution, and implementing it. You will also be responsible for building within and contributing to a targeting platform to ensure solutions are reusable, robust, and tested.

Responsibilities include, but are not limited to:

Leadership:

• Lead the development of targeting models using statistical, machine learning, and causal modeling techniques
• Work with business stakeholders to scope new projects and build on current projects, taking ownership of data science projects from end to end (data collection to model deployment)
• Serve as a team expert in statistical methods, applied machine learning, and causal modeling

Machine Learning and Causal Modeling Expertise:

• Possess a strong understanding of the differences between inferential, predictive, and prescriptive models and experience applying methods in all three areas
• Stay up-to-date with the latest developments in machine learning and causal modeling and apply these techniques where appropriate
• Enhance and maintain machine learning platform
• Contribute to and build new internal packages to democratize machine learning and build reusable solutions
• Monitor and evaluate the performance of machine learning models and algorithms, and implement improvements as necessary

Communication and Collaboration:

• Translate complex problems and solutions to all levels of the organization
• Manage processes and platforms in the algorithmic targeting space

Salary Range: $165,000 - $190,000

Qualifications

• PhD, MS, or 2+ years research experience in computational social science, applied mathematics, cognitive and neural sciences, economics, information retrieval, statistics, or another quantitative/computational discipline
• 4+ years of combined experience in advanced analytics in industry or research experience
• Advanced level knowledge of statistical methods and machine learning. Ability to define the direction for a project and select appropriate methods and tools using up to date knowledge of recent advancements
• Experience managing machine learning projects from end-to-end
• Experience using data visualization tools and techniques to deliver and present business insights and value
• Experience designing performance metrics and using machine learning for feature engineering
• Experience implementing scalable systems using Google Cloud (GCP) or similar cloud platform.
• Proficient in Python and SQL

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.

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