Senior Data Scientist

Grubhub

Senior Staff Data Scientist at Grubhub applying machine learning for marketplace efficiency and customer experience. Collaborating with teams to implement data-driven strategies and mentoring scientists.

Posted 6/4/2026full-timeNew York City • Illinois, New York • 🇺🇸 United StatesSenior💰 $240,000 - $249,500 per yearWebsite

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

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.
Lead the exploration of interconnected marketplace systems, recognizing feedback loops between customer behavior, fulfillment reliability, ETA accuracy, pricing, supply planning, product experience, and business performance.
Develop causal inference and experimentation frameworks that help Wonder understand which product, operational, and marketplace changes truly drive business impact.
Partner with engineering to drive architecture decisions for shared data layers, feature pipelines, modeling APIs, experimentation infrastructure, and production ML services.
Define and implement robust experimentation strategies for changes that move business metrics in high-noise environments.
Champion business-impact-driven data science, integrating causal inference, experimentation, risk-aware modeling, and scalable production ML systems that learn and adapt.

Requirements

What you’ll need

8+ years of industry experience with MS or 6+ years with PhD in Statistics, Economics, Applied Mathematics, Computer Science, Data Science, Machine Learning, or a related quantitative field.
Proven experience applying data science and machine learning to complex business problems, such as marketplace optimization, customer experience, forecasting, personalization, pricing, supply/demand balancing, operational policy changes, or product experimentation.
Deep expertise in causal inference, experimentation, and statistical modeling, including methods such as A/B testing, difference-in-differences, regression discontinuity, instrumental variables, synthetic controls, uplift modeling, or causal impact analysis.
Strong intuition for business and product trade-offs — customer experience vs. efficiency, ETA confidence vs. conversion risk, fulfillment reliability vs. cost, marketplace growth vs. quality, and short-term optimization 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 best practices.
Fluency in SQL or similar tools for directly interrogating production-scale datasets.
Experience mentoring and providing technical direction to other scientists, analysts, or engineers.

Benefits

Comp & perks

competitive salary package including equity and 401K
multiple medical, dental, and vision plans to meet all of our employees' needs
many benefits and perks that are not listed

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data sciencemachine learningcausal inferencestatistical modelingA/B testingregression discontinuityuplift modelingPythonSQLobject-oriented design

Soft Skills

mentoringcoachingtechnical directionbusiness intuitiontrade-off analysis