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
As part of the Media Group Decision Sciences team, the 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, the recommender system, automated marketing, personalized advertisement, commerce and revenue optimization systems, customer journey and CRM solutions. In this role, the Lead Data Scientist will use advanced data science methodologies including causal discovery analysis, reinforcement learning, machine learning models, Bayesian analysis etc. and work closely with business owners, teammates and engineers to build a state-of-the-art real-time video streaming service.

Qualifications

• Advanced (Master or PhD) degree with specialization in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research or another quantitative field or equivalent.
• 5+ years of experience in statistical methods and machine learning within industry and research.
• Understanding of algorithmic complexity of model training and testing, particularly for real-time and near real-time models.
• Has strong knowledge of causal inference techniques, Gen AI (LLM) implementation, or reinforcement learning.
• Solid technical knowledge of A/B testing methodologies, experimental design, statistics and other analytical concepts.
• Experience implementing scalable, distributed, and highly available systems using Google Cloud.
• Proficient in Python and S

• Lead development of analytical models using statistical, machine learning and data mining methodologies. Advise, help to resolve issues and handle non-standard cases.
• Define procedures for cleansing, discretization, imputation, selection, generalization etc. to create high quality features for the modeling process.
• Effectively communicate with team members, project partners and business stakeholders on goals, procedures, timelines and expectations.
• Proactively anticipate/identify upcoming issues and take initiatives to provide solutions
• Use big data, relational and non-relational data sources to access data at the appropriate level of granularity for the needs of specific analytical projects. Maintain up to date knowledge of the relevant data set structures and participate in defining necessary upgrades and modifications.
• 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 work on improving the codebase and machine learning lifecycle infrastructure

Qualifications

• Advanced (Master or PhD) degree with specialization in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research or another quantitative field or equivalent.
• 5+ years of experience in statistical methods and machine learning within industry and research.
• Understanding of algorithmic complexity of model training and testing, particularly for real-time and near real-time models.
• Has strong knowledge of causal inference techniques, Gen AI (LLM) implementation, or reinforcement learning.
• Solid technical knowledge of A/B testing methodologies, experimental design, statistics and other analytical concepts.
• Experience implementing scalable, distributed, and highly available systems using Google Cloud.
• Proficient in Python and SQ