We create world-class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our theme parks and consumer experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, MSNBC, CNBC, NBC Sports, Telemundo, NBC Local Stations, Bravo, USA Network, and Peacock, our premium ad-supported streaming service. We produce and distribute premier filmed entertainment and programming through Universal Filmed Entertainment Group and Universal Studio Group, and have world-renowned theme parks and attractions through Universal Destinations & Experiences. NBCUniversal is a subsidiary of Comcast Corporation.

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. Our Diversity, Equity and Inclusion initiatives, coupled with our Corporate Social Responsibility work, is informed by our employees, audiences, park guests and the communities in which we live. We strive to foster a diverse, equitable and inclusive culture where our employees feel supported, embraced and heard. Together, we’ll continue to create and deliver content that reflects the current and ever-changing face of the world.

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.

As part of the Direct-to-Consumer Decision Sciences team, this Director, Data Science will be responsible for creating algorithmic targeting solutions across the app, including promotion pricing.

In this role, the Director, Data Science will build and deploy machine learning solutions at scale to empower and optimize leadership’s and our research partners’ abilities to lift our enterprise metrics by best leveraging 1st party data to personalize the user experience and our apps’ dynamic surfaces.

Our Principals and Directors serve as a team leader in advanced statistical and machine learning methodologies and lead both data scientists and projects to create analytical solutions for multiple business verticals.

Responsibilities include, but are not limited to:

• Own and deliver results on existing and new complex projects related to the development of targeting models using machine learning and causal uplift modeling
• Serve as a team expert in statistical methods and applied machine learning
• Drive the collection and manipulation of new data and the refinement of existing data sources
• Possess a strong understanding of the differences between inferential, predictive, and prescriptive models and experience applying methods in all three areas
• Work with business stakeholders to define priorities, approaches and business requirements for data science solutions and experiments
• Translate complex problems and solutions to all levels of the organization
• Manage processes, platforms, and people in the algorithmic targeting space
• Drive innovation of the methodologies and tools used by the team

• PhD, MS, or 5+ years research experience in computational social science, applied mathematics, cognitive and neural sciences, economics, information retrieval, statistics, or another quantitative/computational discipline
• 7+ years of combined experience in advanced analytics in industry or research experience (preferably in the uplift, causal, and/or treatment effect modelling field)
• Experience in leading small teams on commercial projects.
• 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 (especially those that include contextual bandits and policy optimization)
• 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.
• Expert in Python and SQL

Desired Characteristics:

• Experience with ownership of data products, either internal or consumer-facing
• Experience owning data pipelines and machine learning pipelines using airflow
• Experience in a subscription and active user-driven business
• 3+ years of people management experience in data science or machine learning engineering
• Strong oral and written communication skills
• Excitement for selling and presenting Machine Learning to drive product development
• Team oriented and collaborative approach with a demonstrated aptitude and willingness to mentor and teach
• Pride and ownership in your team’s work and confident representation of your team to other parts of NBCUniversal

Hybrid: This position has been designated as hybrid, generally contributing from the office a minimum of three days per week.

This position is eligible for company sponsored benefits, including medical, dental and vision insurance, 401(k), paid leave, tuition reimbursement, and a variety of other discounts and perks. Learn more about the benefits offered by NBCUniversal by visiting the Benefits page of the Careers website. Salary range: $200,000-$250,000, Bonus and LTI eligible

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. 

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