Senior Data Scientist

About the Opportunity

Position: Senior Staff Data Scientist – Wunder Data Science

Location: New York, Chicago, Denver (hybrid – 3 days in office, up to 5 days if desired)

Summary: As a Senior Staff Data Scientist at Wunder, you will shape the strategic direction of applied data science, mentor a growing team, and collaborate across engineering, product, and business to build scalable, production‑grade systems. Your work will focus on high‑leverage opportunities across the marketplace, including customer experience, operational efficiency, ETA accuracy, pricing strategy, supply planning, demand forecasting, and business impact measurement.

• Serve as a technical thought leader, defining principles, frameworks, and best practices for data science, experimentation, and machine learning.
• Mentor and coach senior and junior scientists, fostering career development and technical excellence.
• Explore interconnected marketplace systems, recognizing feedback loops between customer behavior, fulfillment reliability, ETA accuracy, pricing, supply planning, product experience, and performance.
• Design and implement robust experimentation strategies and causal inference frameworks that drive business metrics in high‑noise environments.
• Partner with engineering to influence architecture decisions for shared data layers, feature pipelines, modeling APIs, experimentation infrastructure, and production ML services.
• Champion business‑impact‑driven data science, integrating causal inference, experimentation, risk‑aware modeling, and scalable production ML systems.

• 8+ years of industry experience with MS degree 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 (e.g., A/B testing, difference‑in‑differences, regression discontinuity, instrumental variables, synthetic controls, uplift modeling, causal impact analysis).
• Strong intuition for business and product trade‑offs (e.g., customer experience vs. efficiency, ETA confidence vs. conversion risk).
• Proficiency in Python, scalable, production‑ready code, SQL or similar tools, and visualization.
• Experience deploying data science, ML, or causal inference systems into production, partnering on architecture, deployment, and monitoring.
• Demonstrated mentoring and technical leadership with other scientists, analysts, or engineers.

• Leading end‑to‑end design of data science, machine learning, measurement, or experimentation frameworks within marketplace, consumer product, fulfillment, logistics, pricing, forecasting, or operations systems.
• Designing causal measurement strategies for complex systems where product, marketplace, and operational decisions interact across multiple layers.
• Background in Bayesian modeling, econometrics, or observational measurement in high‑noise environments.
• Experience building or influencing production ML systems that combine predictive modeling, causal measurement, experimentation, and business rules.
• Influencing across disciplines to align product, engineering, operations, business, and data science around cohesive ML, experimentation, and measurement strategy.
• Defining strategy and technical roadmaps for data science, ML, experimentation, or causal inference platforms.

Our hybrid model requires 3 days a week in the office. Many team members choose to come in more often to take advantage of in‑person collaboration and connection. You’re encouraged to be in the office up to 5 days a week if it works for you.

New York: $240,000–$249,500 per year. Illinois: $216,000–$224,500 per year. Salary is geographic‑specific and may vary based on location, skills, education, and experience.

We offer a competitive salary package including equity and 401(k). Multiple medical, dental, and vision plans are available along with various other benefits and perks. We are committed to diversity, equity, and inclusion and do not discriminate based on protected classes.

We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, military service eligibility, veteran status, marital status, disability, or any other protected class. We participate in the federal government’s E‑Verify program and will provide accommodations during the interview process if needed.