Principal Data Scientist

Job Description

NBCUniversal is one of the world's leading media and entertainment companies.
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
The Media Group at NBCU supports a powerhouse collection of consumer-first brands including Peacock, NBC, Bravo, NBC Sports, and NBCU International. 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 a key member of the Decision Sciences team, the Principal Data Scientist will create analytical solutions for various verticals of NBCU's video streaming service. This includes, but is not limited to, dynamic pricing, messaging optimization, CRM solutions, and customer value assessment.
In this role, the Principal Data Scientist will employ advanced data science methodologies such as causal uplift modeling, contextual and non-contextual bandits, experimentation, and Gen AI (LLMs). They will collaborate closely with business owners, teammates, and engineers to develop state-of-the-art algorithmic targeting solutions for a dynamic media platform. Additionally, 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:
• Own and deliver results on complex projects related to the development of analytical models using machine learning, causal uplift modeling, contextual bandits, and Gen AI techniques.
• Provide mentorship to teammates through pairing and code reviews.
• Serve as a technical lead for the team; stay updated on state-of-the-art methods and help apply them as needed.
• Communicate work and project implications effectively to stakeholders of varying technical expertise.
• Develop templates and examples for the team on coding, readmes, and presentation materials.
• Conduct rigorous cross-validation, backtesting, and offline policy evaluation of machine learning models.
• Expertise with CI/CD processes and contribute to a sustainable and robust codebase.
• Experience with batch jobs/data pipelines and comfortable deploying through systems like Airflow, Luigi, and Composer.
• Build and interact with production systems for serving machine learning predictions, including real-time systems like TensorFlow Extended (TFX) pipelines and TensorFlow Serving.
• Work cross-functionally across data, engineering, and product teams to launch and maintain machine learning-driven projects.
Qualifications
• Advanced (Master's or PhD) degree with specialization in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research, or another quantitative field, or equivalent.
• 5-8 years of combined experience in data science in industry or research.
• Expert knowledge of standard data science and statistical techniques.
• Expertise in two of the following: causal inference techniques, Gen AI (LLM) implementation, or contextual bandits.
• Experience implementing scalable systems (Google Cloud preferred).
• Proficiency with data visualization tools and techniques.
• Ability to work with stakeholders to drive project ideas and turn them into rigorous solutions.
• Expert knowledge of Python and SQL.

Desired Characteristics:
• Proven experience working 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).
• Demonstrated ability to implement and own end-to-end data projects with a diverse group of stakeholders.
• Experience building and working with low response time machine learning APIs for use cases such as search, recommendations, or prediction.
• Proven track record of serving as the ''tech lead'' for a stakeholder-facing data science team.
• Experience contributing to unit, integration, and data integrity tests for a machine learning codebase.
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: $185,000-$220,000, bonus and LTI eligible

Jobcode: Reference SBJ-z39znn-18-97-14-90-42 in your application.