Senior Data Analyst, Toast

• You love solving complex problems and getting to the truth of what motivates guests
• You are grounded in the numbers, comfortable tying together marketing, product, and behavioral data, and skilled at translating insights into clear, actionable recommendations
• Bachelor’s degree in Business, Economics, Computer Science, Information Systems, or a quantitative field with 6+ years of experience in Data Analytics, Growth Analytics, Marketing Analytics, or Product Analytics; Master’s degree with 4+ years experience; or equivalent experience
• Strong SQL skills and experience with statistical analysis and modeling (e.g. Python, R)
• Understanding of growth funnels and B2C customer metrics, including acquisition, activation, engagement, retention, and LTV at a company that has achieved scale
• Hands-on experience working with various data platforms (e.g. Snowflake, Amplitude, Heap) and tools for querying, visualization, etc. (e.g. Looker, Hex, Sigma, Tableau)
• Experience designing and maintaining metrics that bridge marketing performance and product usage
• Proven ability to QA data and ensure accuracy, consistency, and trust in reporting
• Ability to translate stakeholder questions into clear analytical approaches, dashboards, and actionable insights
• Experience supporting experimentation, A/B testing, and behavioral analytics across both marketing and product surfaces
• Strong communication and storytelling skills, with the ability to distill complex data into clear recommendations for technical and non-technical audiences
• A self-starter mindset—comfortable building new analytics foundations and iterating on them in a fast-moving environment

Desirable

• As a Senior Data Analyst on the Consumer team at Toast, you’ll report to the head of Consumer Growth
• You’ll work at the intersection of product-led growth metrics and marketing analytics to drive Growth and support the Consumer, Product, Lifecycle, Marketing and Engineering teams in understanding how guests discover, adopt, and engage with Toast products
• You will build measurement frameworks, dashboards, and analyses that connect acquisition channels with in-product behavior and downstream outcomes, slice/dice relevant data for action, and identify the highest-impact growth segments
• We operate like a small startup within Toast with a strong focus on experimentation, testing, and iteration
• Getting the data right is essential to scaling consumer growth
• Your work will directly inform growth strategy and execution and influence how we attract, convert, and retain consumers
• Your data informs strong decision-making and continuously improves both acquisition efficiency and the consumer product experience
• You’ll partner with data engineers, product managers, and marketers to define and measure the guest journey in data
• You’ll create reports and visualizations to elevate key results
• Most importantly, you’ll deliver scalable insights that the consumer team can use to acquire, retain and delight guests of Toast restaurants
• Write SQL queries and leverage analytics tools to create datasets and baseline reports that fuel growth; support funnel analysis, cohort analysis, attribution, experimentation, and revenue reporting
• Partner with product and functional teams to deliver analyses, datasets, and metrics that measure the full funnel across consumer acquisition, activation, engagement, retention, and monetization
• Connect marketing channel performance (paid, owned, and earned) with in-product behavior, conversion, and long-term customer value to inform product-led growth strategies
• Build scalable dashboards and self-serve reporting that give teams clear visibility into growth performance across channels and product surfaces
• Proactively identify trends, anomalies, and risks across the growth funnel
• Support and influence an experimentation culture by defining success metrics and analyzing A/B/n tests across both marketing touchpoints and in-product experiences
• Act as a trusted analytics partner, bringing your own insights and recommendations to department reviews, roadmap discussions, and leadership forums
• Work cross-functionally with Engineering, Business Intelligence, and Data Platform teams as needed to ensure integrity and reliability of underlying data
• Enable self-service analytics by documenting key metrics, improving data discoverability, and training stakeholders on analytics tools and best practices