Senior Data Scientist - Ads Auctions
Instacart · United States
- Hybrid
- Full-time
- $204,500 / year
- United States
Job highlights
- Innovate and enhance ad auction mechanisms for transparency.
- Develop CPC infrastructure and bidding algorithms.
- Design analytical frameworks for auction systems.
- Run experiments and build predictive models.
- Collaborate with Engineering, ML, and Product teams.
About the role
About Instacart
At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team. There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.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.
Compensation and Benefits
Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here. Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here. For US based candidates, the base pay ranges for a successful candidate are listed below. CA, NY, CT, NJ: $194,000—$204,500 USD. WA: $185,000—$195,500 USD. OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI: $177,000—$187,000 USD. All other states: $161,000—$170,000 USD.Key skills/competency
- Data Science
- Auction Mechanisms
- Bidding Algorithms
- Marketplace Pricing
- CPC Optimization
- Machine Learning
- Statistical Modeling
- Causal Inference
- Econometrics
- Experimentation
Skills & topics
- Data Scientist
- Ads Auctions
- Marketplace
- Bidding Algorithms
- CPC Optimization
- Machine Learning
- Statistical Modeling
- Causal Inference
- Econometrics
- Experimentation
- Python
- R
- SQL
- Remote
How to get hired
- Tailor your resume: Highlight experience in ads, auctions, or marketplace pricing systems, emphasizing quantitative roles and relevant projects.
- Showcase technical skills: Detail your proficiency in SQL and Python/R, along with experience in statistical modeling and machine learning.
- Demonstrate domain expertise: Emphasize hands-on experience with auction mechanics, bidding systems, and experimental design in your application.
- Prepare for interviews: Be ready to discuss your approach to mechanism design, causal inference, and translating business needs into analytical solutions.
- Understand Instacart's mission: Align your application with Instacart's values and commitment to transforming the grocery industry and providing flexible work.
Technical preparation
Master complex SQL queries for data extraction.,Write efficient Python or R code for modeling.,Develop statistical and ML models for auctions.,Practice causal inference and econometrics techniques.
Behavioral questions
Describe a complex analytical framework you designed.,How do you translate business needs into models?,Share an experience influencing cross-functional teams.,Discuss a time you navigated a dynamic environment.
Frequently asked questions
- What does a Senior Data Scientist on the Ads Auctions team at Instacart do?
- As a Senior Data Scientist on the Ads Auctions team at Instacart, you will be a core technical contributor responsible for innovating and enhancing auction mechanisms. This includes developing CPC infrastructure, optimizing bidding algorithms, designing analytical frameworks, running experiments, and building statistical and machine learning models to improve advertiser performance and Instacart's ads revenue.
- What are the minimum qualifications for the Senior Data Scientist - Ads Auctions role at Instacart?
- The minimum qualifications include 5+ years of experience in a quantitative role, with exposure to ads, auctions, or marketplace pricing systems. You should have hands-on experience with auction mechanics, CPC/CPM bidding systems, or bid optimization. Proficiency in SQL and Python/R, and the ability to design and run rigorous experiments are also required.
- What preferred qualifications will make a candidate stand out for this role?
- Preferred qualifications include deep familiarity with auction theory, mechanism design, or algorithmic pricing, as well as experience building or analyzing large-scale CPC/CPM bidding systems. An awareness of business trade-offs in multi-sided marketplaces and confidence in collaborating with cross-functional senior stakeholders are also highly valued. An MS/PhD in a quantitative field is a plus.
- Is the Senior Data Scientist - Ads Auctions position at Instacart remote?
- Yes, the Senior Data Scientist - Ads Auctions position at Instacart is a remote role, aligning with Instacart's 'Flex First' policy. This means employees have the flexibility to choose where they work, whether from home, an office, or another location, while staying connected through regular in-person events.
- What is the expected salary range for a Senior Data Scientist - Ads Auctions at Instacart in the US?
- The base pay range for this role in the US varies by location. For example, in CA, NY, CT, NJ, it ranges from $194,000 to $204,500 USD. In WA, it's $185,000 to $195,500 USD. For other states, the range is $161,000 to $170,000 USD. Offers are dependent on factors like experience, skills, and permanent work location. The role is also eligible for equity grants.
- What kind of experiments will a Senior Data Scientist conduct at Instacart?
- A Senior Data Scientist will run rigorous experiments to evaluate the impact of auction mechanism changes. This includes analyzing variations like bid shading, different auction pricing models (e.g., second-price vs. generalized second-price), and dynamic pricing strategies, translating the results into actionable recommendations for system improvements.