Senior Data Scientist II - Ads Optimization
About this role
Inefficient ad pacing and budget allocation can severely limit revenue and platform balance in a multi-billion dollar ecosystem. Instacart needs a Senior Data Scientist to design and operate the decision-making engine behind its multi-billion-dollar ads business, ensuring that supply and demand meet efficiently. This person will drive analytics, experimentation, and algorithmic strategy across pacing, targeting, and budgeting systems that directly impact platform revenue and advertiser outcomes.
The Ads Optimization team builds the systems responsible for bidding, pacing, budgeting, and targeting that convert advertiser goals into real-time outcomes. Working at the intersection of data science, economics, and production systems, this team member will own the full research-to-production loop from problem framing and modeling to experimentation and measurement in live environments. Ideal candidates possess a strong data science background with hands-on ads optimization experience at scale, excellent cross-functional communication skills, and the ability to bridge complex technical findings for business leadership.
What you will do
- Own the analytics and experimentation strategy for pacing, targeting, and related optimization areas to drive measurable improvements in advertiser outcomes.
- Design and build intelligent pacing algorithms and budget allocation systems using adaptive control and model-predictive control techniques for production environments.
- Lead end-to-end experimentation by designing frameworks, diagnosing complex signals, and translating results into actionable recommendations for leadership.
- Apply causal inference, statistical modeling, and machine learning techniques to optimize how ad spend is distributed across time and auction opportunities.
- Present findings and strategic recommendations to product, engineering, and data science leadership.
- Serve as a technical anchor and thought leader in ads optimization by setting analytical standards and mentoring peers.
- Collaborate with ads product and sales teams to gather advertiser feedback and inform optimization priorities.
What you need
- Proven experience in ads optimization at an ad tech company with hands-on work in pacing, targeting, or budget allocation systems.
- Strong foundation in product and data analysis, A/B experimentation, causal inference, and statistical modeling.
- Demonstrated experience shipping optimization systems into production with real measurement and iteration in live environments.
- Excellent communication skills with the ability to synthesize complex technical findings for senior business and engineering stakeholders.
- At least 6 years of professional work experience in a data science or related technical field.
Nice to have
- Experience collaborating directly with ads product or sales teams, or with advertisers, to shape product and algorithmic priorities
- Background in budget-constrained allocation methods, adaptive control, or model-predictive control in production systems
Benefits
- New hire equity grant
- Annual refresh grants
Skills and tech stack
Questions candidates ask
What is the remote work policy for this role?
Instacart operates under a Flex First remote work policy where employees have the flexibility to choose where they do their best work. Currently, hiring for this position is restricted to candidates residing in Ontario, Alberta, British Columbia, and Nova Scotia.
What is the compensation range for this position?
The base pay range for a successful Canadian candidate is $192,000 to $202,500 CAD. Offers may vary based on factors such as candidate experience and permanent work location.
What additional financial compensation is included besides base pay?
This role is eligible for a new hire equity grant as well as annual refresh grants. Market-competitive compensation and benefits are provided based on the employee's work location.
What kind of team will I be working with?
You will operate on the Ads Optimization team, which serves as the decision-making engine of a $1B+ ads business. You will partner closely with Product, Engineering, Machine Learning, and Sales teams.