Senior Staff Data Scientist

Salary: $216,000 - 249,500 per year Requirements:

• Were looking for 8+ years of industry experience with an MS, or 6+ years with a PhD, in Statistics, Economics, Applied Mathematics, Computer Science, Data Science, Machine Learning, or a closely related quantitative discipline.
• We need a strong track record applying data science and machine learning to complex business challenges such as marketplace optimization, customer experience, forecasting, personalization, pricing, supply-demand balancing, operational policy changes, or product experimentation.
• Were seeking deep expertise in causal inference, experimentation, and statistical modeling, including approaches like A/B testing, difference-in-differences, regression discontinuity, instrumental variables, synthetic controls, uplift modeling, or causal impact analysis.
• We value a sharp understanding of business and product trade-offs, including customer experience versus efficiency, ETA confidence versus conversion risk, fulfillment reliability versus cost, marketplace growth versus quality, and short-term optimization versus long-term health.
• We require proficiency in Python, data analysis, visualization, and production-ready object-oriented code.
• Were looking for demonstrated success taking data science, machine learning, or causal inference systems into production, working with engineering on architecture, deployment, and monitoring practices.
• We need fluency in SQL or similar tools for working directly with production-scale datasets.
• Were looking for experience mentoring others and providing technical direction to scientists, analysts, or engineers.
• Preferred qualifications include experience leading end-to-end design of data science, machine learning, measurement, or experimentation frameworks in marketplace, consumer product, fulfillment, logistics, pricing, forecasting, or operations settings.
• Additional preferred experience includes designing causal measurement strategies for complex systems where product, marketplace, and operational decisions interact across multiple layers.
• We also value a background in causal inference, econometrics, Bayesian modeling, experimental design, or observational measurement in high-noise environments.
• Preferred experience includes applied experimentation frameworks such as A/B testing, power analysis, heterogeneous treatment effects, guardrail metrics, interference effects, and long-term impact measurement.
• Experience building or influencing production ML systems that combine predictive modeling, causal measurement, experimentation, and business rules is a plus.
• We value the ability to align product, engineering, operations, business, and data science around a cohesive ML, experimentation, and measurement strategy.
• Experience defining strategy and technical roadmaps for data science, machine learning, experimentation, or causal inference platforms is also highly desirable.

• Well rely on you to serve as a technical thought leader in Data Science by defining principles, frameworks, and best practices for how we use data, experimentation, and machine learning to improve customer, marketplace, and business outcomes.
• Youll mentor and coach a growing team of Data Scientists and help drive career development and technical excellence across the group.
• Youll lead exploration of interconnected marketplace systems, identifying feedback loops between customer behavior, fulfillment reliability, ETA accuracy, pricing, supply planning, product experience, and business performance.
• Youll develop causal inference and experimentation frameworks that help us determine which product, operational, and marketplace changes truly drive business impact.
• Youll partner with engineering to shape architecture decisions for shared data layers, feature pipelines, modeling APIs, experimentation infrastructure, and production ML services.
• Youll define and implement robust experimentation strategies for changes that affect business metrics in high-noise environments.
• Youll champion business-impact-driven data science by integrating causal inference, experimentation, risk-aware modeling, and scalable production ML systems that learn and adapt.

• Machine Learning
• Python
• SQL

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hackajob is working with Grubhub to connect exceptional professionals with this opportunity. Grubhub, now part of Wonder, is a leading U.S. ordering and delivery marketplace with more than 415,000 merchants across over 4,000 cities. The company is based in New York City, Chicago, and Denver, and operates with a renewed startup-style momentum. This Senior Staff Data Scientist role sits within Wonder Data Science, where the mission is to build data science and machine learning systems that improve marketplace performance, customer experience, and decision-making. The role offers a hybrid schedule with three days per week in the office, with the option to come in up to five days a week for in-person collaboration. Compensation is geographically structured, with New York listed at $240,000 to $249,500 per year and Illinois at $216,000 to $224,500 per year, alongside a competitive package that includes equity, 401(k), and medical, dental, and vision coverage.

last updated 37 week of 2026