Senior Manager of CS Data & Analytics, Toast

• This role is ideal for a player-coach who is energized by ambiguous problems, works iteratively, and isn’t only one kind of data person
• Heir home base is analytics, with a real interest in data science and analytics engineering. They don’t need to be an expert in either, just passionate about expanding their knowledge, something AI tools now put within reach for anyone
• Experience: 8+ years in analytics, BI, or data science, including 2+ years leading analysts, with a track record of owning a recurring executive business review and turning ambiguous questions into scoped, answerable analyses
• Hands-on experience extracting insight from unstructured data such as survey verbatims or support transcripts
• Working comfort with statistics and experimental design. You’ve dabbled in data science, such as running a regression to find what drives NPS or a classification model to find themes in text, and you know control groups, matched cohorts, and pre/post baselining. You use these methods for exploratory work and partner with a data scientist on anything production-grade
• Strong SQL, fluency with a modern data stack (Snowflake, Hex, dbt, or equivalent), and a clear point of view on data visualization and what makes a dashboard or analytical artifact useful
• A tinkerer and builder with hands-on experience using AI for analytics, whether to speed up analysis, automate recurring work, or build self-serve tools for stakeholders
• Direct experience with customer success, customer experience, or support data (NPS/CSAT programs, ticket and contact data, CRM), ideally in SaaS or restaurant technology
• Ability to translate analysis into clear recommendations for senior leaders, and to push back constructively when a question can’t be answered cleanly

Desirable

• The Customer Success Data & Analytics (CSDA) team sets the standards for how data is used across Customer Success, building the foundational data and tooling that help CS deliver a better, more efficient customer experience. With a data engineering team rebuilding the CS data model and an Applied AI & Data Science lead embedded on the team, we’re building what analytics looks like in the AI era
• As Senior Manager, Customer Success & Experience Analytics, you’ll be the analytics partner to CS leadership, shaping how the organization understands its performance and its customers, with a focus on customer experience and enablement
• Reporting to the Senior Director of CS Data & Analytics, you’ll lead two analysts and bring a holistic customer view by connecting data across Care, Onboarding, Enablement, and Product
• Run the Customer Success Business Review: Own the tools and mechanisms behind the weekly review, driving rigorous but efficient inspection of key business indicators and hosting insightful discussions with business owners about their successes and challenges
• Lead Analytics for Customer Experience & Voice of the Customer: Be a major contributor to the CX and VOC programs by owning the analytics behind them: the reporting, insights, and recommendations that help the business improve how customers experience Toast. Go beyond what the numbers say to why they move, making sure we measure and manage the right inputs for the outcomes we care about. Use survey verbatims, contact transcripts, and other unstructured data alongside traditional metrics
• Measure Education & Enablement Impact: Own the framework connecting training, self-service content, and in-product guidance to ticket reduction, self-service, and adoption. Design test-and-control measurement, set baselines before programs launch, and drive a data-first culture in customer education
• Lead the Team & Shape the Data Foundation: Grow a team of talented analysts and support the ownership they bring to their areas. Run a transparent intake and prioritization process, and expand self-service through AI tooling and well-documented data. Partner with data engineering on the CS data model rebuild, and bring the Applied AI & Data Science lead well-framed problems worth modeling