Product Owner – Enterprise Data Science

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

NBCUniversal’s Enterprise Product Team builds products that provide essential capabilities to organizations throughout NBCUniversal. The team leverages deep relationships with our business engagement and engineering counterparts to build cohesive, end-to-end solutions for their clients or users. The product portfolio is aligned around critical NBCU functions such as Content/Title Management, Data & Analytics, Scheduling & Distribution, and Content Sales.

As a part of the Product team, you will be responsible to support our Ad Sales Data Science teams.  You will enable them to leverage Data Platform products focused on creating and delivering cutting-edge data solutions that empower our organization to make data-driven decisions and drive innovation.

At our core, we are an organization dedicated to building and maintaining robust and scalable data platforms that serve as the foundation for our data-driven initiatives.

We are passionate about creating a data ecosystem that fosters collaboration, empowers data scientists and analysts, and unlocks the value of our vast data assets. By leveraging state-of-the-art technologies, best practices, and industry standards, we aim to deliver data platforms that are efficient, secure, and reliable.

In our organization, we embrace the principles of Data Mesh, recognizing the importance of decentralizing data ownership and empowering domain experts. We believe in democratizing access to data, enabling self-service capabilities, and promoting data governance practices that ensure data quality, compliance, and security.

As a team, we work closely with various stakeholders, including data scientists, engineers, business leaders, privacy, legal, governance, and other product teams. Collaboration, effective communication, and a strong customer-centric mindset are our guiding principles as we gather requirements, prioritize features, and deliver value incrementally.

Together, we drive the strategic roadmap for our data platforms, continuously seeking opportunities for improvement, innovation, and optimization. We stay abreast of emerging technologies, industry trends, and evolving data needs to ensure that our organization remains at the forefront of the data landscape.

Essential Responsibilities

As a Product Owner, your responsibilities will involve working closely with both Data Scientists and Engineering teams to ensure the successful development and delivery of data science products and solutions. Here the detailed responsibilities:

1. Product Ownership:
   • Define and communicate the product vision and strategy for the data platform, aligned with the organization’s overall goals and objectives. Continuously refine and evolve the product vision based on feedback from stakeholders, market trends, and emerging technologies.
   • Defining and prioritizing the product backlog helps maintain focus on high-impact features and improvements.
   • Lead backlog refinement sessions and sprint planning meetings helps ensure that Engineering teams understand and can execute the requirements effectively.
   • Creating and maintaining user stories, acceptance criteria, and other product documentation ensures clarity and alignment across teams.
   • Conducting product and user research enables data-driven decision-making and identifies areas for product enhancements.
2. Cross-functional Collaboratio