Senior Data Scientist II - Ads Optimization
Quick Summary
6+ years of professional experience in data science or a related quantitative field, with proven experience working on advertising optimization at an ad technology company or comparable environment.
This is a senior data science role focused on optimizing a large-scale advertising business through experimentation, analytics, economics, and algorithmic decision-making. You will help shape how advertising demand and supply interact across bidding, pacing, targeting, budgeting, and related optimization systems. Your work will directly influence advertiser outcomes, platform efficiency, user experience, and revenue performance. You will partner closely with Product, Engineering, Machine Learning, Data Science, and Sales teams to move ideas from research and modeling into production. The role combines rigorous experimentation and causal analysis with hands-on development of optimization systems operating in high-throughput environments. It also offers the opportunity to serve as a technical thought leader and mentor while influencing the strategic direction of ads optimization.
- Own the analytics and experimentation strategy for pacing, targeting, budget allocation, and related advertising optimization areas, driving measurable improvements in advertiser outcomes and platform efficiency.
- Design and develop intelligent pacing algorithms and budget allocation systems using adaptive control, model-predictive control, and related optimization techniques for high-throughput production environments.
- Lead end-to-end experimentation across optimization systems, including experiment design, measurement, signal diagnosis, interpretation, and translation of results into actionable recommendations.
- Apply causal inference, statistical modeling, and machine learning techniques to optimize how advertising spend is distributed across time and auction opportunities.
- Balance advertiser objectives, user experience, platform efficiency, and revenue considerations when developing and evaluating optimization strategies.
- Partner closely with Product, Engineering, Machine Learning, Data Science, and Analytics teams to take concepts from problem framing and research through production deployment, measurement, and iteration.
- Present complex analytical findings, experiment results, and strategic recommendations clearly to senior Product, Engineering, and Data Science stakeholders.
- Act as a technical anchor and thought leader within the Ads Optimization space, helping establish analytical standards and mentoring other data scientists and team members.
- Collaborate with Ads Product and Sales teams to gather advertiser feedback, understand business needs, and translate market insights into optimization priorities.
Requirements
~1 min read- 6+ years of professional experience in data science or a related quantitative field, with proven experience working on advertising optimization at an ad technology company or comparable environment.
- Hands-on experience with advertising systems such as pacing, targeting, bidding, budget allocation, or related optimization mechanisms.
- Strong foundation in product and data analytics, A/B experimentation, causal inference, statistical modeling, and quantitative problem solving.
- Demonstrated experience shipping optimization systems into production, including measuring their performance and iterating based on real-world results rather than focusing solely on research.
- Strong understanding of how experimentation and statistical analysis can inform decisions in complex, high-scale production environments.
- Excellent communication skills, with the ability to synthesize sophisticated technical findings and explain their business implications to senior technical and non-technical stakeholders.
- Strong cross-functional collaboration skills and the ability to influence product and engineering priorities through rigorous analysis and evidence.
- Experience working directly with advertising product teams, sales teams, or advertisers to shape product and algorithmic priorities is a plus.
- Background in budget-constrained allocation, adaptive control, model-predictive control, or related optimization methods in production systems is desirable.
- Ability to operate independently on ambiguous problems while maintaining strong analytical rigor, business judgment, and attention to measurable outcomes.
What We Offer
~2 min readLocation & Eligibility
Listing Details
- Posted
- September 29, 2026
- First seen
- September 29, 2026
- Last seen
- September 29, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 68%
- Scored at
- September 29, 2026
Signal breakdown
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