About the company
Instacart is transforming the grocery industry, delivering an essential service that customers rely on for groceries and household goods, while offering flexible earnings opportunities to Personal Shoppers. Instacart is a Flex First team, allowing employees to choose where they do their best work.
Responsibilities
- Own the analytics and experimentation strategy for pacing, targeting, and related optimization areas, driving measurable improvements in advertiser outcomes and platform efficiency
- Design and build intelligent pacing algorithms and budget allocation systems grounded in adaptive control and model-predictive control techniques, deployed in high-throughput production environments
- Lead end-to-end experimentation across optimization systems — designing experiment frameworks, diagnosing complex or conflicting signals, and translating results into clear, actionable recommendations for Product and Engineering leadership
- Apply causal inference, statistical modeling, and ML techniques to optimize how ad spend is distributed across time and auction opportunities, balancing user experience, advertiser goals, and platform revenue
- Present findings and strategic recommendations to leadership across Product, Engineering, and Data Science
- Serve as a thought leader and technical anchor in the Ads Optimization space, setting the analytical standard and mentoring peers across the team
- Collaborate with the Ads Product and Sales teams to gather advertiser feedback and inform optimization priorities
Requirements
- Proven experience in ads optimization at an ad tech company (e.g., Google, Meta, Amazon, TikTok, or equivalent), with hands-on work in pacing, targeting, budget allocation, or related systems
- Strong data science foundation: product and data analysis, A/B experimentation, causal inference, and statistical modeling
- Experience shipping optimization systems into production — not just research, but real measurement and iteration in live environments
- Excellent communication skills, with the ability to synthesize complex technical findings for senior business and engineering stakeholders
- 6+ years of work experience in a data science or related field
- Preferred: Experience collaborating directly with an ads product or sales team, or with advertisers, to shape product and algorithmic priorities
- Preferred: Background in budget-constrained allocation methods, adaptive control, or model-predictive control in production systems
Conditions
- Remote position in the United States
- Base pay range: $182,000 - $230,000 USD per year depending on location
- Eligible for new hire equity grant and annual refresh grants
- Market-competitive compensation and benefits