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 Collaboration:
   • Acting as a liaison between Data Science and Engineering teams promotes effective communication and collaboration, fostering a cohesive working environment.
   • Collaborate with Data Science teams to define and refine data collection and data preprocessing strategies, ensuring the availability of high-quality and relevant data for model development.
   • Collaborating with Engineering teams to define technical specifications and feasibility aligns product features with technical capabilities.
   • Providing guidance and support to Data Scientists and Engineering teams throughout the product development lifecycle helps streamline the process and address any challenges.
   • Fostering a collaborative and productive working environment among different teams involved in data product development enhances overall productivity and outcomes.
3. Product Development and Delivery:
   • Defining and measuring product success metrics ensures that the product is meeting its intended goals.
   • Monitoring and analyzing user feedback and data product usage patterns help identify areas for improvement and prioritize enhancements.
   • Prioritizing bug fixes, enhancements, and new feature development based on user feedback and business priorities helps maintain a user-centric approach.
   • Collaborate with the Engineering team and other stakeholders to plan and coordinate releases. Define release scope, manage release schedules, and ensure proper documentation and communication of new features and enhancements.
   • Coordinating and participating in user testing and feedback sessions ensures that the product features are validated and meet user needs.
4. Stakeholder Management:
   • Regularly communicating with stakeholders and providing progress updates helps maintain transparency and alignment.
   • Seeking feedback from stakeholders and incorporating it into the product roadmap and backlog ensures that their perspectives and needs are considered.
   • Collaborating with stakeholders to ensure alignment between business goals, user needs, and technical feasibility helps drive successful outcomes and maximize value.
5. Data Science Domain Expertise:
   • Developing a strong understanding of data science principles, methodologies, and tools enables effective collaboration and support for Data Scientists.
   • Hands-on data exploration and analyses of large data to enable data-driven stories and product features.
6. Continuous Learning and Improvement:
   • Stay up-to-date with advancements in data science, machine learning, and AI technologies, and identify opportunities to incorporate them into product development and actively seeking opportunities to enhance your knowledge and skills to drive personal growth and improving your effectiveness in the role.
7. Product Documentation and Training:
   • Contributing to the development of product documentation tailored to the needs of Data Science teams helps ensure clarity and ease of use.
   • Documenting best practices, guidelines, and usage instructions for utilizing the data platform effectively promotes consistent and optimal utilization.
   • Providing training and support to Data Science teams helps enhance their capabilities and maximizes the value they can derive from the platform.

Qualifications

• Education: Bachelor's degree in Computer Science, Data Science, or a related field. A Master's degree is a plus.
• Previous Experience:
  • 5+ years full-time, post-graduation work experience in data analytics, media research, or data science with ad tech company, digital entertainment company, advertising agency, media research provider or data analytics firm.
  • Demonstration of independently accomplished data science projects from end to end including feature engineering, visualization, statistical modeling.
• Technical Skills:
  • Strong understanding of data science concepts, machine learning algorithms, and statistical techniques.
  • Experience in cloud platforms and data warehouses (AWS, Snowflake, etc.).

Remote Workers: This position has been designated as fully remote, meaning that the position is expected to contribute from a non-NBCUniversal worksite, most commonly an employee’s residence.

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: $100,000 - $130,000 (bonus 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.

If you are a qualified individual with a disability or a disabled veteran, you have the right to request a reasonable accommodation if you are unable or limited in your ability to use or access nbcunicareers.com as a result of your disability. You can request reasonable accommodations in the US by calling 1-818-777-4107 and in the UK by calling +44 2036185726.