Senior Manager, Data Science & Analytics

About Sesame Workshop

Sesame Workshop is the global nonprofit behind Sesame Street and so much more. For over 50 years, we have worked at the intersection of education, media, and research, creating joyful experiences that enrich minds and expand hearts, all in service of empowering each generation to build a better world. Our beloved characters, iconic shows, outreach in communities, and more bring playful early learning to families in more than 190 countries and advance our mission to help children everywhere grow smarter, stronger, and kinder.

Learn more atwww.sesame.organd follow Sesame Workshop on Instagram,Tik Tok, Facebook, and X.

The Senior Manager, Data Science & Analytics is a member of Research & Insights and reports to the Senior Director, Data Science. This is the first dedicated hire within the Data Science function and acts as the product owner for Sesame Workshop's shared data models and analytics layer. While the knowledge of what each source contains lives with its data owners across the business, this role knows that landscape end-to-end, documents it, and turns it into maintainable, well-modeled data products in dbt that the organization's data analysts and business-intelligence (BI) partners build on.

This role owns the models and their trustworthiness, while those analysts own how the data is presented to stakeholders.

Sesame Workshop is building its internal data capabilities to better serve teams across the organization: from Marketing and Strategy to Revenue and Impact Programs. The Senior Manager, Data Science & Analytics exists to own data models, transformation logic, and metric standards that turn raw, scattered data into a dependable analytics layer.

This is a product-ownership role for the analytics layer. The right candidate is quick to learn and adapt to the ever-changing data landscape, documents how each measure is calculated and to what quality standard, and encodes it as versioned, maintainable data products in dbt. This provides the backbone that lets analysts turn well-modeled data into dashboards, reports, and presentations.

This is a hands-on, senior individual-contributor role with room to grow into broader technical leadership and data governance. The Senior Manager operates independently, is well organized, sets standards rather than waiting for direction, and finishes things: taking prototypes or proofs of concept and turning them into data products that run reliably. As Sesame Workshop's data practice matures, the role is positioned to own data governance operations for the organization.

• Own the data models and documentation that encode the organization's key metrics, capturing, from each source system's data owners, which source answers which question, how each measure (e.g., "reach," "engagement," "revenue") is calculated, and the quality bar it must meet.
• Build and maintain the data models and transformation logic (e.g., dbt) that implement those definitions, turning proof-of-concept analyses and prototype tools into documented, tested, version-controlled data products that downstream users can depend on without ongoing intervention.
• Manage data quality and documentation as a product, maintaining a catalog of the active data models and metrics (their sources, refresh schedules, and known limitations), keeping metric definitions and methodology transparent and easy to inspect (such as dbt docs) so the numbers are understood and trusted across teams, and proactively flagging data source changes or data-quality issues before they reach downstream users.
• Build and maintain shared datasets that combine and standardize data from across the organization's source systems, so analysts can work from consistent, reliable data and build their own reports rather than manually pulling and reconciling exports.
• Integrate and model data from multiple systems, including but not limited to local databases, cloud object storage, Google Analytics, and Salesforce, into unified, reusable datasets that feed leadership-level and board reporting.
• Improve the performance and reliability of the analytics layer by automating manual workflows, optimizing queries and downstream extracts and data preparation (e.g., for BI tools), and recommending improvements to data-collection practices.
• This role may perform other related duties as needed to support team and organizational priorities.

Collaboration and teamwork:

• Partner with the Senior Director, Data Science, to set the roadmap for shared data products, prioritize what gets modeled, and align the analytics layer with the function's strategic initiatives.
• Coordinate with the Technology team on data infrastructure, access, and governance, and leverage shared platforms such as Snowflake.
• Partner with data analysts and BI colleagues across departments (e.g., Consumer Insights, Marketing) as the internal customers of the analytics layer, so that data products serve the questions teams needed to answer.

Stakeholder and…