Senior Staff Data Scientist
Senior Staff Data Scientist at Grubhub (part of Wonder) shaping applied data-science strategy for a US food-ordering and delivery marketplace. Day to day: design causal inference and experimentation frameworks, work on ETA accuracy, pricing, and supply/demand forecasting, mentor scientists, and partner with engineering to take ML systems to production using Python and SQL.
- Compensation
- $216K–$249.5K / yr
- Location
- New York, United States
- Work setup
- Onsite
- Seniority
- Staff
- Employment
- Not specified
- Experience
- 6+ years
- Category
- Data science
- Posted
Skills
Must have
- 8+ years industry experience with MS, or 6+ years with PhD in Statistics, Economics, Applied Mathematics, Computer Science, Data Science, Machine Learning, or related quantitative field
- Proven experience applying data science and ML to complex business problems (marketplace optimization, customer experience, forecasting, personalization, pricing, supply/demand balancing, operational
- Deep expertise in causal inference, experimentation, and statistical modeling (A/B testing, difference-in-differences, regression discontinuity, instrumental variables, synthetic controls, uplift mode
- Strong intuition for business and product trade-offs (customer experience vs. efficiency, fulfillment reliability vs. cost, short-term vs. long-term health)
- Proficiency in Python, data analysis, visualization, and writing scalable production-ready code using object-oriented design
- Demonstrated ability to take data science, ML, or causal inference systems into production, partnering with engineering on architecture, deployment, and monitoring
- Fluency in SQL or similar tools for directly interrogating production-scale datasets
- Experience mentoring and providing technical direction to other scientists, analysts, or engineers
- Ability to work hybrid, 3 days a week in the office
Nice to have
- Experience leading end-to-end design of data science, ML, measurement, or experimentation frameworks in marketplace, consumer product, fulfillment, logistics, pricing, forecasting, or operations syste
- Experience designing causal measurement strategies for complex systems where product, marketplace, and operational decisions interact
- Background in causal inference, econometrics, Bayesian modeling, experimental design, or observational measurement in high-noise environments
- Experience with applied experimentation frameworks: power analysis, heterogeneous treatment effects, guardrail metrics, interference effects, long-term impact measurement
- Experience building or influencing production ML systems combining predictive modeling, causal measurement, experimentation, and business rules
- Influence across disciplines — aligning product, engineering, operations, business, and data science around a cohesive strategy
- Experience defining strategy and technical roadmaps for data science, ML, experimentation, or causal inference platforms
Full description
About Grubhub
At Grubhub, we believe food is more than just a meal: It’s a source of discovery, connection, and pure enjoyment. There’s a time and place for every type of dish, from hidden neighborhood gems to tried-and-true favorites, and we exist to connect people with the food they love in all the ways they like to dig in. We’ve been at it since 2004, but now, as part of Wonder, Grubhub is operating with a renewed sense of momentum and the high-velocity energy of a powerhouse startup.
As a leading U.S. ordering and delivery marketplace, we feature over 415,000 merchants in more than 4,000 cities, creating the ultimate food experience by elevating online ordering through innovative restaurant technology, easy-to-use platforms, and an improved delivery experience. We are constantly finding new ways to innovate—from integrated grocery delivery with groceries powered by Instacart to exclusive loyalty programs. Join our team, based out of New York City, Chicago and Denver, and help us give our diners the exceptional value they deserve.
About the Opportunity
At Wonder Data Science, our mission is to build data science and machine learning systems that improve how our marketplace operates, how customers experience the platform, and how the business makes high-quality decisions. As a Senior Staff Data Scientist, you will go beyond individual problem solving — you will help shape the strategic direction of applied data science, mentor senior and junior scientists, and collaborate closely with engineering, product, operations, and business leaders to move our ML and analytics capabilities toward scalable, production-grade systems.
You will identify high-leverage opportunities across the business, including marketplace efficiency, customer experience, ETA accuracy, fulfillment reliability, pricing strategy, supply planning, demand forecasting, and operational performance. You will design statistically rigorous frameworks to understand causal impact, separate signal from noise, and guide business strategy through experimentation, measurement, and principled inference.
You will help define how we structure trade-offs like customer experience vs. operational efficiency, speed vs. cost, prediction accuracy vs. business impact, short-term metric movement vs. long-term marketplace health, and automation vs. human judgment. You’ll prototype, experiment, influence architecture, and ensure we operationalize models and insights that actually move business metrics — not just analyses that look good offline.
The Impact You Will Make
- Serve as a technical thought leader in Data Science — defining principles, frameworks, and best practices for how Wonder uses data, experimentation, and machine learning to improve customer, marketplace, and business outcomes.
- Mentor and coach a growing team of Data Scientists and contribute to career development and technical excellence across the group.