Sr. Lead Data Scientist

Company Description

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.

Job Description

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 Decision Sciences team, the Sr. Lead Data Scientist will be responsible for creating analytical solutions for one or more verticals of NBCU's video streaming service including, but not limited to, dynamic pricing, messaging optimization, CRM solutions, and customer value assessment.

In this role, the Sr. Lead Data Scientist will use advanced data science methodologies including causal uplift modeling, contextual and non-contextual bandits, experimentation, and Gen AI (LLMs). They will work closely with business owners, teammates and engineers to build state-of-the-art algorithmic targeting solutions for a dynamic media platform. They will be responsible for building, maintaining, and testing robust production ready systems that may need to serve low latency predictions.

Responsibilities include, but are not limited to:

• Lead existing and develop new projects related to the development of analytical models using machine learning, causal uplift modeling, and Gen AI techniques.
• Provide mentorship to teammates via pairing and code reviews
• Expertly communicates work and project implications to stakeholders of varying technical expertise
• Conduct rigorous cross-validation and backtesting of model performance.
• Proficiency with CI/CD processes and contributes to a sustainable and robust codebase
• Experience with batch jobs/data pipelines and is comfortable deploying through these systems (i.e. Airflow, Luigi, Composer)
• Build and interact with production systems for serving machine learning predictions.

Qualifications

• Advanced (Master or PhD) degree with specialization in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research or another quantitative field or equivalent.
• 3-5 years of combined experience in data science in industry or research.
• Has expert knowledge of standard data science and statistical techniques
• Has a track record of successful deployment of machine learning models, frameworks, and their training, prediction time, and implications on production systems
• Has strong knowledge of two of causal inference techniques, Gen AI (LLM) implementation, or contextual bandits
• Experience implementing scalable systems (Google Cloud preferred).
• Experience with data visualization tools and techniques.
• Ability to develop ideas with stakeholders and turn them into rigorous solutions
• Proficient in Python and SQL

Desired Characteristics

• Working experience with product teams to deploy prescriptive machine learning models to drive one or more KPIs.
• Knowledge of enterprise-level digital analytics platforms (e.g. Adobe Analytics, Google Analytics, etc.)
• Implementing and owning end-to-end data projects with a diverse group of stakeholders
• Knowledge of best practices with unit and data testing
• Familiarity with low latency apis for Machine Learning inference

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: $165,000-$190,000, bonus and LTI eligible

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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