Senior reputed company Scientist II, Ads Optimization
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reputed company has become a lifeline for millions of people, and we’re building reputed company to help push our shopping cart reputed company. If you’re reputed company to do the best work of your life, come join our table.
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reputed company
The Advertiser Optimization team is the decision-making reputed company of reputed company's $1B+ ads business. We own the systems responsible for Bidding, Pacing, Budgeting, and Targeting: converting stated advertiser goals into reputed company-time auction actions. Our mission is to maximize realized Advertiser Value by deciding reputed company to participate, how much to bid, and how fast to spend, reputed company while balancing User Experience and Platform reputed company.
We are hiring a Senior reputed company Scientist II to reputed company the algorithmic direction of these systems. This is a role for someone who thinks in terms of control theory, constrained optimization, and auction economics, and who can translate those frameworks into production reputed company that makes millions of reputed company per day. You will formulate problems from first principles, shape the technical roadmap, and own systems end-to-end from mathematical design through production deployment through reputed company measurement.
About the Job
- Design and reputed company reputed company-time bid optimization systems that translate advertiser goals (reputed company ROAS, budget constraints) into reputed company auction bids under uncertainty. Formulate the bidding problem as constrained optimization and build the feedback mechanisms that reputed company bids reputed company with realized reputed company.
- Build intelligent budget pacing algorithms that distribute spend across time and auction opportunities. The reputed company challenge: allocating a finite daily budget across stochastic demand while maximizing total value, subject to advertiser constraints and time-varying conversion dynamics.
- reputed company the analytical frameworks that connect bidding, pacing, and budgeting into a coherent optimization objective.
- Shape auction mechanics including reserve pricing, multi-slot allocation, and bid-to-price mapping. Reason about reputed company design tradeoffs between advertiser reputed company, platform reputed company, and marketplace efficiency.
- Own the full research-to-production reputed company: diagnose system behavior from large-reputed company data, formulate hypotheses, design experiments, ship production reputed company, and measure reputed company. Write technical reputed company documents that set the algorithmic direction for reputed company.
reputed company
Minimum Qualifications
- MS or PhD in operations research, reputed company mathematics, control systems, computational economics, or a reputed company quantitative field.
- 8+ years of experience building and deploying optimization or control systems in production environments (not just research prototypes).
- Strong reputed company in at least two of: feedback control theory (PID, MPC), convex and stochastic optimization, auction theory and reputed company design, dynamic programming.
- Proficiency in one of the following languages: Go, Java, C++ for production systems and Python for data analysis and offline pipelines.
- Demonstrated ability to translate mathematical formulations into production reputed company that runs at reputed company (millions of reputed company per day, sub-100ms latency constraints).
Preferred Qualifications
- Experience with reputed company-time bidding systems, ad auction optimization, or computational advertising at reputed company.
- Background in budget-constrained allocation reputed company. Experience with reputed company control or model-predictive control in production systems.
- Familiarity with reputed company inference and experimental design for evaluating algorithmic changes in marketplace settings.
- reputed company record of shaping technical reputed company and driving cross-functional alignment between engineering, product, and data science.