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.

#LI-Remote

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.

#LI-Remote

Overview

This is a general posting for multiple Senior Data Science roles open across our 4-sided marketplace. Roles are open at both the L5 (Senior Data Scientist I) and L6 (Senior Data Scientist II) levels. You’ll get the chance to learn about the different problems the Data Science team solves as you go through the process. Towards the end of your process, we’ll do a team-matching exercise to determine which of the open roles/teams you’ll join. At the bottom of this posting, you’ll find a breakdown of the currently open roles.

About the Job

• Own analytical frameworks that guide the product roadmap.
• Design rigorous experiments and interpret results to draw detailed and actionable conclusions.
• Develop statistical models to extract trends, measure results, and predict future performance of our products.
• Build simulations to project the impact of various product and policy interventions.
• Enable objective decision-making across the company by democratizing data through dashboards and other analytical tools.
• Use expertise in causal inference, machine learning, complex systems modeling, behavioral decision theory, etc., to shape the future of Instacart.
• Present findings in a compelling way to influence Instacart’s leadership.

About You

Minimum Qualifications

• 5+ years of experience working in a quantitative role at a product company or a research organization.
• Ability to run rigorous experiments and generate scientifically sound recommendations.
• Ability to write complex, efficient, and eloquent SQL queries to extract data.
• Ability to write efficient and eloquent code in Python or R.
• A desire to build and improve consumer software products.
• Ability to translate business needs into analytical frameworks.
• Eagerness to learn, flexibility to pivot when needed, savviness to navigate a dynamic environment, and a growth mindset to build a successful team and company.

Preferred Qualifications

• Awareness of business trade-offs when working on a multi-sided marketplace.
• Confidence in collaborating with and influencing cross-functional stakeholders (e.g., Product, Engineering) at a senior level.
• MS/PhD in Statistics, Economics, Applied Mathematics, or a related field.

Currently Opened Roles

Ads Auctions | Sr. Data Scientist I (L5)

The Ads Auctions team is responsible for innovating and enhancing auction mechanisms to create a competitive and transparent marketplace that benefits both advertisers and consumers. In this role, you’ll own analytical frameworks and simulations that shape the evolution of our CPC pricing, bid optimization, and auction selection processes—running rigorous experiments to evaluate mechanism changes such as bid shading and dynamic pricing. You’ll partner closely with Engineering, ML, and Product to translate business needs into well-specified model requirements, and apply expertise in auction theory, mechanism design, and econometrics to ensure our systems are fair, efficient, and aligned with marketplace goals.

AI for Analytics | Sr. Data Scientist II (L6)

Instacart is developing AI-powered systems to accelerate analytical work and enable self-serve analytics at scale, with a goal of 2x-ing the number of features launched by end of 2026. As a Senior Data Scientist II, you’ll own product strategy and AI expertise—identifying high-impact opportunity areas and deploying AI and ML systems in production settings. This is a senior cross-functional leadership role: you’ll shape the product roadmap, ruthlessly prioritize across competing stakeholders, and set the analytical direction for how Instacart’s data experts and AI systems work together.

Order Experiences (Search) | Sr. Data Scientist I (L5)

The Order Experiences (Search) team is focused on making it fast and effortless for customers to find the right items and complete their order with confidence. As a Senior Data Scientist, you’ll own the analytics and experimentation strategy that powers how we interpret customer intent and surface the most relevant results—driving search conversion, order rate, and GTV. You’ll partner closely with Product, Engineering, and ML to shape the roadmap for search relevance and ranking quality, running experiments across retrieval, ranking, and search UX while connecting offline model evaluation to real-world business outcomes.

Ecosystems | Sr. Data Scientist II (L6)

The Ecosystems team tackles some of Instacart’s most strategic macro-level analytical challenges, including quantifying the impact of economic trends, competitive dynamics, and seasonality on core business metrics. As a Senior Data Scientist II, you’ll own time-series forecasting for key business outcomes, develop measurement frameworks for evaluating competing growth initiatives, and build AI tooling to scale analytics workflows across the team. This role also carries a technical leadership dimension—you’ll set the methodological bar, mentor peers, and review analyses to drive rigor across the organization.

Delivery | Sr. Data Scientist II (L6)

The Delivery team is dedicated to ensuring customers receive their complete orders seamlessly, spanning the full flow from capturing customer information to coordinating the shopper experience. As a Senior Data Scientist II, you’ll identify strategic opportunities to enhance the delivery experience, design and execute rigorous experiments to evaluate new product features, and leverage geospatial data and advanced analytical techniques to optimize logistics. You’ll also proactively identify high-risk delivery scenarios and develop solutions to the underlying systemic issues that drive them.

Marketing | Sr. Data Scientist I (L5)

The Marketing Data Science team is responsible for measurement and optimization across Instacart’s paid digital channels, including search, shopping, display, social, and video. As a Senior Data Scientist, you’ll build and maintain sophisticated attribution models—including multi-touch and incrementality-based approaches—and develop scalable data pipelines to turn raw marketing data into clean, analysis-ready datasets. You’ll apply causal inference methods such as geo holdouts and difference-in-differences to evaluate campaign effectiveness, partnering closely with marketing, data engineering, and business teams to define measurement frameworks and drive data-informed decisions. You'll also model user lifetime value (LTV) across acquisition cohorts, quantifying how marketing spend and channel mix influence long-term retention and monetization to inform budget allocation and growth strategy

#LI-Remote

Overview

This is a general posting for multiple Senior Data Science roles open across our 4-sided marketplace. Roles are open at both the L5 (Senior Data Scientist I) and L6 (Senior Data Scientist II) levels. You’ll get the chance to learn about the different problems the Data Science team solves as you go through the process. Towards the end of your process, we’ll do a team-matching exercise to determine which of the open roles/teams you’ll join. At the bottom of this posting, you’ll find a breakdown of the currently open roles.

About the Job

• Own analytical frameworks that guide the product roadmap.
• Design rigorous experiments and interpret results to draw detailed and actionable conclusions.
• Develop statistical models to extract trends, measure results, and predict future performance of our products.
• Build simulations to project the impact of various product and policy interventions.
• Enable objective decision-making across the company by democratizing data through dashboards and other analytical tools.
• Use expertise in causal inference, machine learning, complex systems modeling, behavioral decision theory, etc., to shape the future of Instacart.
• Present findings in a compelling way to influence Instacart’s leadership.

About You

Minimum Qualifications

• 5+ years of experience working in a quantitative role at a product company or a research organization.
• Ability to run rigorous experiments and generate scientifically sound recommendations.
• Ability to write complex, efficient, and eloquent SQL queries to extract data.
• Ability to write efficient and eloquent code in Python or R.
• A desire to build and improve consumer software products.
• Ability to translate business needs into analytical frameworks.
• Eagerness to learn, flexibility to pivot when needed, savviness to navigate a dynamic environment, and a growth mindset to build a successful team and company.

Preferred Qualifications

• Awareness of business trade-offs when working on a multi-sided marketplace.
• Confidence in collaborating with and influencing cross-functional stakeholders (e.g., Product, Engineering) at a senior level.
• MS/PhD in Statistics, Economics, Applied Mathematics, or a related field.

Currently Opened Roles

Ads Auctions | Sr. Data Scientist I (L5)

The Ads Auctions team is responsible for innovating and enhancing auction mechanisms to create a competitive and transparent marketplace that benefits both advertisers and consumers. In this role, you’ll own analytical frameworks and simulations that shape the evolution of our CPC pricing, bid optimization, and auction selection processes—running rigorous experiments to evaluate mechanism changes such as bid shading and dynamic pricing. You’ll partner closely with Engineering, ML, and Product to translate business needs into well-specified model requirements, and apply expertise in auction theory, mechanism design, and econometrics to ensure our systems are fair, efficient, and aligned with marketplace goals.

AI for Analytics | Sr. Data Scientist II (L6)

Instacart is developing AI-powered systems to accelerate analytical work and enable self-serve analytics at scale, with a goal of 2x-ing the number of features launched by end of 2026. As a Senior Data Scientist II, you’ll own product strategy and AI expertise—identifying high-impact opportunity areas and deploying AI and ML systems in production settings. This is a senior cross-functional leadership role: you’ll shape the product roadmap, ruthlessly prioritize across competing stakeholders, and set the analytical direction for how Instacart’s data experts and AI systems work together.

Order Experiences (Search) | Sr. Data Scientist I (L5)

The Order Experiences (Search) team is focused on making it fast and effortless for customers to find the right items and complete their order with confidence. As a Senior Data Scientist, you’ll own the analytics and experimentation strategy that powers how we interpret customer intent and surface the most relevant results—driving search conversion, order rate, and GTV. You’ll partner closely with Product, Engineering, and ML to shape the roadmap for search relevance and ranking quality, running experiments across retrieval, ranking, and search UX while connecting offline model evaluation to real-world business outcomes.

Ecosystems | Sr. Data Scientist II (L6)

The Ecosystems team tackles some of Instacart’s most strategic macro-level analytical challenges, including quantifying the impact of economic trends, competitive dynamics, and seasonality on core business metrics. As a Senior Data Scientist II, you’ll own time-series forecasting for key business outcomes, develop measurement frameworks for evaluating competing growth initiatives, and build AI tooling to scale analytics workflows across the team. This role also carries a technical leadership dimension—you’ll set the methodological bar, mentor peers, and review analyses to drive rigor across the organization.

Delivery | Sr. Data Scientist II (L6)

The Delivery team is dedicated to ensuring customers receive their complete orders seamlessly, spanning the full flow from capturing customer information to coordinating the shopper experience. As a Senior Data Scientist II, you’ll identify strategic opportunities to enhance the delivery experience, design and execute rigorous experiments to evaluate new product features, and leverage geospatial data and advanced analytical techniques to optimize logistics. You’ll also proactively identify high-risk delivery scenarios and develop solutions to the underlying systemic issues that drive them.

Marketing | Sr. Data Scientist I (L5)

The Marketing Data Science team is responsible for measurement and optimization across Instacart’s paid digital channels, including search, shopping, display, social, and video. As a Senior Data Scientist, you’ll build and maintain sophisticated attribution models—including multi-touch and incrementality-based approaches—and develop scalable data pipelines to turn raw marketing data into clean, analysis-ready datasets. You’ll apply causal inference methods such as geo holdouts and difference-in-differences to evaluate campaign effectiveness, partnering closely with marketing, data engineering, and business teams to define measurement frameworks and drive data-informed decisions. You'll also model user lifetime value (LTV) across acquisition cohorts, quantifying how marketing spend and channel mix influence long-term retention and monetization to inform budget allocation and growth strategy

#LI-Remote

Overview

Instacart’s Shopping Experience team is focused on making it fast and effortless for customers to find the right items within a single retailer and complete their order with confidence. As a Senior Data Scientist dedicated to Search, you’ll own the analytics and experimentation strategy that powers how we interpret customer intent and connect it to the most relevant items and retailers.

In this role, you’ll partner closely with Product, Engineering, and Machine Learning to shape the roadmap for search relevance, ranking quality, and latency. Your work will translate complex, noisy signals into clear insights and recommendations that move the metrics that matter—search conversion, order rate, and GTV—while also strengthening downstream experiences like ads and retailer satisfaction.

About the Job

• Own core Search metrics and funnels end to end (e.g., query → impression → engagement → cart adds), including defining guardrails, monitoring performance across platforms and segments, and diagnosing conversion gaps.
• Design, run, and interpret experiments across ranking, retrieval, and search UX (e.g., relevance model changes, query understanding, result layouts), turning ambiguous or conflicting outcomes into crisp, data-driven recommendations.
• Partner with Product, Engineering, and ML to prioritize opportunities, size impact, and influence the roadmap for relevance, quality, and latency improvements that unlock measurable business outcomes.
• Build deep diagnostic analyses by query class, price point, surface, and customer lifecycle to pinpoint where and why Search underperforms and specify concrete changes that will move key outcomes.
• Connect offline model evaluation with online and business metrics by collaborating with ML partners on evaluation design, ensuring model changes reliably improve end-user experience—not just offline scores.
• Improve data quality, instrumentation, and metric definitions for Search so that teams can reason about performance with clarity, consistency, and speed.

About You

You combine rigorous analytics, strong product sense, and clear communication to drive decisive action in a fast-paced environment. You enjoy rolling up your sleeves, collaborating across disciplines, and using experimentation to uncover what truly helps customers find the right items quickly.

Minimum Qualifications

• 5+ years of experience in data science or product analytics, with a track record of impact on consumer-facing products.
• Advanced SQL proficiency, including complex joins and window functions, working with large-scale datasets in modern data warehouses (e.g., Snowflake, BigQuery, Redshift).
• Proficiency in Python or R for analysis, experimentation, and modeling.
• Hands-on experience designing and analyzing A/B tests end to end, including metric selection, power and sample sizing, covariate adjustment, and decision-making under uncertainty.
• Demonstrated ability to define success metrics, decompose ambiguous product problems, and deliver clear, opinionated recommendations to Product and Engineering partners.
• Excellent written and verbal communication skills; able to tailor complex analyses for both technical and non-technical audiences.
• Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Economics, Engineering) or equivalent practical experience.
• Comfort using modern AI tooling (e.g., Claude, code assistants, PromptQL) to accelerate analysis, experimentation, and communication while exercising strong judgment on quality and reliability.

Preferred Qualifications

• Experience in search relevance, ranking, recommendations, personalization, or information retrieval (e.g., e-commerce or marketplace search).
• Familiarity with NLP, embeddings, and semantic search, including how to evaluate and iterate on these techniques in production.
• Experience bridging offline evaluation metrics (e.g., NDCG, precision/recall, human evaluation) with online experiments and business outcomes.
• Background in causal inference beyond standard A/B tests (e.g., holdouts, diff-in-diff, quasi-experiments) to measure long-term or cross-surface effects.
• Comfort working across web and native app surfaces, navigating tradeoffs between relevance, monetization, and latency.
• Proven impact improving logging, instrumentation, and metric definitions in complex data environments.

#LI-Remote

Overview

Instacart’s Shopping Experience team is focused on making it fast and effortless for customers to find the right items within a single retailer and complete their order with confidence. As a Senior Data Scientist dedicated to Search, you’ll own the analytics and experimentation strategy that powers how we interpret customer intent and connect it to the most relevant items and retailers.

In this role, you’ll partner closely with Product, Engineering, and Machine Learning to shape the roadmap for search relevance, ranking quality, and latency. Your work will translate complex, noisy signals into clear insights and recommendations that move the metrics that matter—search conversion, order rate, and GTV—while also strengthening downstream experiences like ads and retailer satisfaction.

About the Job

• Own core Search metrics and funnels end to end (e.g., query → impression → engagement → cart adds), including defining guardrails, monitoring performance across platforms and segments, and diagnosing conversion gaps.
• Design, run, and interpret experiments across ranking, retrieval, and search UX (e.g., relevance model changes, query understanding, result layouts), turning ambiguous or conflicting outcomes into crisp, data-driven recommendations.
• Partner with Product, Engineering, and ML to prioritize opportunities, size impact, and influence the roadmap for relevance, quality, and latency improvements that unlock measurable business outcomes.
• Build deep diagnostic analyses by query class, price point, surface, and customer lifecycle to pinpoint where and why Search underperforms and specify concrete changes that will move key outcomes.
• Connect offline model evaluation with online and business metrics by collaborating with ML partners on evaluation design, ensuring model changes reliably improve end-user experience—not just offline scores.
• Improve data quality, instrumentation, and metric definitions for Search so that teams can reason about performance with clarity, consistency, and speed.

About You

You combine rigorous analytics, strong product sense, and clear communication to drive decisive action in a fast-paced environment. You enjoy rolling up your sleeves, collaborating across disciplines, and using experimentation to uncover what truly helps customers find the right items quickly.

Minimum Qualifications

• 5+ years of experience in data science or product analytics, with a track record of impact on consumer-facing products.
• Advanced SQL proficiency, including complex joins and window functions, working with large-scale datasets in modern data warehouses (e.g., Snowflake, BigQuery, Redshift).
• Proficiency in Python or R for analysis, experimentation, and modeling.
• Hands-on experience designing and analyzing A/B tests end to end, including metric selection, power and sample sizing, covariate adjustment, and decision-making under uncertainty.
• Demonstrated ability to define success metrics, decompose ambiguous product problems, and deliver clear, opinionated recommendations to Product and Engineering partners.
• Excellent written and verbal communication skills; able to tailor complex analyses for both technical and non-technical audiences.
• Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Economics, Engineering) or equivalent practical experience.
• Comfort using modern AI tooling (e.g., Claude, code assistants, PromptQL) to accelerate analysis, experimentation, and communication while exercising strong judgment on quality and reliability.

Preferred Qualifications

• Experience in search relevance, ranking, recommendations, personalization, or information retrieval (e.g., e-commerce or marketplace search).
• Familiarity with NLP, embeddings, and semantic search, including how to evaluate and iterate on these techniques in production.
• Experience bridging offline evaluation metrics (e.g., NDCG, precision/recall, human evaluation) with online experiments and business outcomes.
• Background in causal inference beyond standard A/B tests (e.g., holdouts, diff-in-diff, quasi-experiments) to measure long-term or cross-surface effects.
• Comfort working across web and native app surfaces, navigating tradeoffs between relevance, monetization, and latency.
• Proven impact improving logging, instrumentation, and metric definitions in complex data environments.

#LI-Remote

Overview

The Ads Auctions team is responsible for innovating and enhancing auction mechanisms to create a competitive and transparent marketplace that benefits both advertisers and consumers. We focus on the full auction workflow—candidate filtering, pricing strategies, bid optimization, and selection processes—with the goal of balancing user experience with advertiser value. As a Senior Data Scientist on this team, you will be a core technical voice shaping how our auction systems evolve, driving improvements to our CPC (cost-per-click) infrastructure and bidding algorithms that directly impact advertiser performance and Instacart's ads revenue.

About the Job

• Design and own analytical frameworks that guide the evolution of our auction and bidding systems, including CPC pricing, bid landscape modeling, and reserve price optimization.
• Run rigorous experiments to evaluate the impact of auction mechanism changes—such as bid shading, second-price vs. generalized second-price auctions, and dynamic pricing—and translate results into actionable recommendations.
• Develop statistical and machine learning models to forecast bid distributions, predict click-through rates, and optimize auction efficiency across advertiser and consumer dimensions.
• Build simulations to model auction dynamics and stress-test proposed mechanism changes before live deployment.
• Partner closely with Engineering, ML, and Product to translate business and advertiser needs into well-specified model and system requirements.
• Enable objective decision-making by building dashboards and monitoring frameworks that surface auction health, advertiser performance, and CPC trends to stakeholders across the organization.
• Apply expertise in causal inference, mechanism design, and econometrics to ensure our auction systems are fair, efficient, and aligned with marketplace goals.
• Present analytical findings and strategic recommendations in a compelling way to influence Instacart's leadership and Ads go-to-market teams.

About You

Minimum Qualifications

• 5+ years of experience working in a quantitative role at a product company or research organization, with meaningful exposure to ads, auctions, or marketplace pricing systems.
• Hands-on experience with auction mechanics, CPC or CPM bidding systems, bid optimization, or related ad monetization problems.
• Ability to run rigorous experiments and generate scientifically sound recommendations in the context of auction or pricing changes.
• Ability to write complex, efficient, and eloquent SQL queries to extract data.
• Ability to write efficient and eloquent code in Python or R.
• A desire to build and improve consumer software products and advertising platforms.
• Ability to translate business needs—from both advertiser and marketplace perspectives—into analytical frameworks.
• Eagerness to learn, flexibility to pivot when needed, savviness to navigate a dynamic environment, and a growth mindset to build a successful team and company.

Preferred Qualifications

• Deep familiarity with auction theory, mechanism design, or algorithmic pricing (e.g., generalized second-price auctions, VCG, bid shading, reserve pricing).
• Experience building or analyzing CPC/CPM bidding systems, budget pacing, or bid landscape models at scale.
• Awareness of business trade-offs when working on a multi-sided marketplace, particularly the interplay between advertiser ROI, consumer experience, and platform revenue.
• Confidence in collaborating with and influencing cross-functional stakeholders (e.g., Product, Engineering, Sales) at a senior level.
• MS/PhD in Statistics, Economics, Operations Research, Applied Mathematics, Computer Science, or a related field.

#LI-Remote

Overview

The Ads Auctions team is responsible for innovating and enhancing auction mechanisms to create a competitive and transparent marketplace that benefits both advertisers and consumers. We focus on the full auction workflow—candidate filtering, pricing strategies, bid optimization, and selection processes—with the goal of balancing user experience with advertiser value. As a Senior Data Scientist on this team, you will be a core technical voice shaping how our auction systems evolve, driving improvements to our CPC (cost-per-click) infrastructure and bidding algorithms that directly impact advertiser performance and Instacart's ads revenue.

About the Job

• Design and own analytical frameworks that guide the evolution of our auction and bidding systems, including CPC pricing, bid landscape modeling, and reserve price optimization.
• Run rigorous experiments to evaluate the impact of auction mechanism changes—such as bid shading, second-price vs. generalized second-price auctions, and dynamic pricing—and translate results into actionable recommendations.
• Develop statistical and machine learning models to forecast bid distributions, predict click-through rates, and optimize auction efficiency across advertiser and consumer dimensions.
• Build simulations to model auction dynamics and stress-test proposed mechanism changes before live deployment.
• Partner closely with Engineering, ML, and Product to translate business and advertiser needs into well-specified model and system requirements.
• Enable objective decision-making by building dashboards and monitoring frameworks that surface auction health, advertiser performance, and CPC trends to stakeholders across the organization.
• Apply expertise in causal inference, mechanism design, and econometrics to ensure our auction systems are fair, efficient, and aligned with marketplace goals.
• Present analytical findings and strategic recommendations in a compelling way to influence Instacart's leadership and Ads go-to-market teams.

About You

Minimum Qualifications

• 5+ years of experience working in a quantitative role at a product company or research organization, with meaningful exposure to ads, auctions, or marketplace pricing systems.
• Hands-on experience with auction mechanics, CPC or CPM bidding systems, bid optimization, or related ad monetization problems.
• Ability to run rigorous experiments and generate scientifically sound recommendations in the context of auction or pricing changes.
• Ability to write complex, efficient, and eloquent SQL queries to extract data.
• Ability to write efficient and eloquent code in Python or R.
• A desire to build and improve consumer software products and advertising platforms.
• Ability to translate business needs—from both advertiser and marketplace perspectives—into analytical frameworks.
• Eagerness to learn, flexibility to pivot when needed, savviness to navigate a dynamic environment, and a growth mindset to build a successful team and company.

Preferred Qualifications

• Deep familiarity with auction theory, mechanism design, or algorithmic pricing (e.g., generalized second-price auctions, VCG, bid shading, reserve pricing).
• Experience building or analyzing CPC/CPM bidding systems, budget pacing, or bid landscape models at scale.
• Awareness of business trade-offs when working on a multi-sided marketplace, particularly the interplay between advertiser ROI, consumer experience, and platform revenue.
• Confidence in collaborating with and influencing cross-functional stakeholders (e.g., Product, Engineering, Sales) at a senior level.
• MS/PhD in Statistics, Economics, Operations Research, Applied Mathematics, Computer Science, or a related field.

#LI-Remote

OVERVIEW

Instacart will increase the number of features launched by 2x by the end of 2026 by effectively using AI. A primary driver of knowing which features to launch includes analytical work traditionally performed by data scientists in collaboration with a product team. We are developing systems to accelerate analyses completed by data experts and enable anyone to self-serve most analytics questions.

ABOUT THE JOB

You would be responsible for driving AI for Analytics data science work which includes:

1. Product strategy: Using data to identify the most promising opportunity areas along with contributing data expertise to refine and develop new product ideas.
2. AI expertise: You will be using and deploying a variety of AI systems in production settings.
3. Intelligent systems: Improving a product feature by adding intelligent functionality to the product that relies on data science methods including statistical and machine learning methods

The role requires strong XFN collaboration where an ideal candidate can:

1. Drive critical efforts to completion with little oversight, while occasionally jumping into roles adjacent to data science (i.e. data engineering, machine learning engineer, etc).
2. Create the product roadmap
3. Ruthlessly prioritize among requests from multiple competing stakeholders
4. Act as a senior cross-functional leader of the team, aligning the team on principles, processes and goals

ABOUT YOU

Minimum Qualifications

• 6+ years of work experience in a data science or related field
• Have deeply engaged with AI workflows
• Expert in Python (pandas), SQL, git, and Jupyter notebooks
• Strong statistical and analytical skills
• Built a machine learning, statistical, or AI model that made its way into production even if the code you wrote was completely rewritten before being deployed

Preferred Qualifications

• 8+ years of work experience in a data science or related field
• Led a cross-functional team to design a system of metrics that connected the business strategy to a set of core metrics and assigned ownership of those metrics to the team
• Significant causal experimentation experience 
• Built a complex machine learning or statistical model and deployed/supported it in production
• Experience with Python (pandas; scikit-learn, statsmodels, or PyTorch; a visualization library that is not matplotlib; a web framework such as flask), SQL (Snowflake), git, Jupyter notebooks

#LI-remote

OVERVIEW

Instacart will increase the number of features launched by 2x by the end of 2026 by effectively using AI. A primary driver of knowing which features to launch includes analytical work traditionally performed by data scientists in collaboration with a product team. We are developing systems to accelerate analyses completed by data experts and enable anyone to self-serve most analytics questions.

ABOUT THE JOB

You would be responsible for driving AI for Analytics data science work which includes:

1. Product strategy: Using data to identify the most promising opportunity areas along with contributing data expertise to refine and develop new product ideas.
2. AI expertise: You will be using and deploying a variety of AI systems in production settings.
3. Intelligent systems: Improving a product feature by adding intelligent functionality to the product that relies on data science methods including statistical and machine learning methods

The role requires strong XFN collaboration where an ideal candidate can:

1. Drive critical efforts to completion with little oversight, while occasionally jumping into roles adjacent to data science (i.e. data engineering, machine learning engineer, etc).
2. Create the product roadmap
3. Ruthlessly prioritize among requests from multiple competing stakeholders
4. Act as a senior cross-functional leader of the team, aligning the team on principles, processes and goals

ABOUT YOU

Minimum Qualifications

• 6+ years of work experience in a data science or related field
• Have deeply engaged with AI workflows
• Expert in Python (pandas), SQL, git, and Jupyter notebooks
• Strong statistical and analytical skills
• Built a machine learning, statistical, or AI model that made its way into production even if the code you wrote was completely rewritten before being deployed

Preferred Qualifications

• 8+ years of work experience in a data science or related field
• Led a cross-functional team to design a system of metrics that connected the business strategy to a set of core metrics and assigned ownership of those metrics to the team
• Significant causal experimentation experience 
• Built a complex machine learning or statistical model and deployed/supported it in production
• Experience with Python (pandas; scikit-learn, statsmodels, or PyTorch; a visualization library that is not matplotlib; a web framework such as flask), SQL (Snowflake), git, Jupyter notebooks

#LI-remote