Data Science Manager, Shopping Experience

Overview

Instacarts Shopping Experience team, part of the Shopping org within Core Experience, owns the end-to-end consumer journey with a single retailer—from storefront and browse, through search and item discovery, into cart and checkout, and all the way to the order status page. We’re focused on building intuitive, data-informed experiences that help customers find what they love, faster.

We’re looking for a Data Science Manager to lead a team of data scientists and shape the analytics and experimentation strategy across critical shopper surfaces including storefront, browse/aisles, search, cart, checkout, OSP, Family, Lists, and Meals/Health. In this highly cross-functional role, you’ll partner closely with Product, Engineering, Design, and Operations to define the right metrics, raise the bar on experiment design and readouts, and deliver insights that drive higher conversion, retention, and satisfaction—while fueling stronger outcomes for retailers and data-grounded AI features.

This is a fast-paced environment with evolving priorities and complex tradeoffs across Enterprise, Lifecycle, Category Growth, and Foundations work. You’ll thrive here if you love rolling up your sleeves, operating with clarity amid ambiguity, and bringing crisp measurement and storytelling to high-impact decisions at scale.

About the Job

• Lead, mentor, and grow a high-performing team of data scientists; set clear priorities, uphold technical excellence, and develop career paths.
• Define and own the analytics and experimentation strategy across storefront, browse/aisles, search, cart, checkout, OSP, Family, Lists, and Meals/Health—covering metrics, guardrails, instrumentation, and experiment best practices.
• Own core shopping metrics and event logging; improve data quality, build reusable dashboards/tools, and ensure reliable, timely insights for decision-making.
• Drive “DS understand projects” that uncover friction in shopping funnels; scope root-cause analyses and partner with PM and Eng to prioritize and ship fixes that move conversion and retention.
• Partner as a thought leader with Product and Engineering leadership to shape roadmaps, make tradeoffs across Enterprise, Lifecycle, Category Growth, and Foundations work, and ensure goals are measurable and achievable.
• Set the bar for experiment design and readouts; coach teams on hypothesis formation, sampling, power analysis, metric selection, and clear storytelling of results and implications.
• Collaborate with ML partners on ranking, recommendations, and personalization initiatives, aligning offline/online evaluation with business outcomes and shopper experience goals.
• Influence and improve cross-functional rituals (e.g., experiment reviews, prioritization forums) to increase speed, rigor, and learning across the organization.
• Ensure AI/agentic features are grounded in robust data and measurement frameworks, with clear definitions of success and long-term impact.

About You

Minimum Qualifications

• 6+ years of experience in data science or analytics, including 2+ years directly managing or tech-leading a data science team in a fast-moving environment.
• Proven track record optimizing consumer app experiences at scale (e.g., funnels, ranking, personalization, experimentation) in technology or similar product-led organizations.
• Deep hands-on expertise in experimentation and measurement, including A/B testing, guardrails, metrics design, and logging/event instrumentation.
• Strong analytical and technical skills with proficiency in SQL and Python or R.
• Experience translating ambiguous customer and retailer problems into clear metrics, analyses, and experiment roadmaps that drive measurable outcomes.
• Demonstrated cross-functional leadership with Product, Engineering, Design, and Operations; able to influence roadmaps and drive alignment without formal authority.
• Track record as a data quality champion—improving instrumentation, building reusable dashboards/tools, and advocating for rigorous yet pragmatic decisions.
• Excellent communication and storytelling skills; able to explain complex tradeoffs and experiment results to non-technical partners and senior stakeholders.

Preferred Qualifications

• Experience in e-commerce, marketplaces, or consumer mobile apps, especially in grocery/retail or multi-retailer environments.
• Background in ranking, recommendation, or personalization systems (e.g., search, recommendations, or personalization platforms) and their evaluation.
• Prior experience standing up or scaling experimentation programs, including tiering, experiment review forums, guardrails, or governance.
• Experience leading or partnering closely with ML teams on production models and offline/online evaluation strategies.
• Success operating in a highly cross-functional, matrixed organization and influencing director+ and VP+ stakeholders.
• Experience defining metric frameworks for complex, multi-surface journeys (e.g., friction metrics, “bad shopping paths,” long-term outcomes).
• Familiarity with GenAI and AI-assisted workflows (e.g., using LLMs for analytics, experimentation tooling, or product features).
• Track record of building data science culture through mentoring, best practices, and process improvements.