Software Engineer II, Advertiser Optimization
Quick Summary
PhD in mathematics, statistics, economics, operations research, or a related quantitative discipline, with a strong foundation in areas such as optimization, probability, statistical modeling,
This role sits at the intersection of large-scale software engineering, quantitative modeling, and digital advertising marketplace optimization. You’ll help build the systems that determine how advertising budgets are allocated, how bids are placed, and how campaigns are paced in real time. Your work will directly influence advertiser value while balancing user experience and platform revenue. You’ll apply concepts from mathematics, statistics, economics, optimization, and related quantitative disciplines to complex marketplace problems. Working alongside experienced scientists, engineers, and product managers, you’ll turn analytical questions into production-ready algorithms and experiments. The role offers meaningful ownership, measurable impact, and exposure to large-scale data and real-time decision systems.
- Develop and evaluate quantitative models and algorithms for advertising bidding, pacing, and budgeting, applying mathematical, statistical, economic, or related quantitative techniques to solve complex marketplace problems at scale.
- Collaborate with senior scientists, engineers, and product managers to translate marketplace questions into mathematical formulations, develop analyses and prototypes, design experiments, and interpret results using large-scale datasets.
- Contribute to production systems by implementing, validating, monitoring, and improving algorithms, progressively taking ownership of well-scoped projects from initial hypothesis through measurable business and technical impact.
- Analyze rapidly changing marketplace conditions and balance analytical rigor with execution speed, adapting to evolving priorities, new challenges, and emerging opportunities.
- Clearly communicate assumptions, methodologies, findings, results, and limitations to both technical and cross-functional stakeholders, helping teams make informed decisions through strong analytical reasoning.
- Support the continuous improvement of systems responsible for real-time bidding, pacing, budgeting, targeting, and advertiser-facing recommendations within a scaled advertising marketplace.
Requirements
~1 min read- PhD in mathematics, statistics, economics, operations research, or a related quantitative discipline, with a strong foundation in areas such as optimization, probability, statistical modeling, econometrics, or control theory.
- Proficiency in Python and SQL, with the ability to translate quantitative concepts into practical analyses, algorithm implementations, experiments, and production-oriented solutions.
- Strong analytical and problem-solving abilities, with the capacity to work through complex quantitative questions and draw meaningful conclusions from large-scale data.
- Excellent written and verbal communication skills, including the ability to explain assumptions, methodologies, results, and limitations clearly to technical and cross-functional audiences.
- 2+ years of software engineering experience, particularly experience applying quantitative methods to production systems, is preferred.
- Familiarity with advertising systems, auction theory, marketplace optimization, or similar decision-making problems is an advantage.
- Experience working with large-scale data pipelines, real-time decision systems, or production machine learning applications is highly valued.
- Familiarity with machine learning techniques and experience applying machine learning methods within production environments is a plus.
What We Offer
~2 min readLocation & Eligibility
Listing Details
- Posted
- September 28, 2026
- First seen
- September 28, 2026
- Last seen
- September 28, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 80%
- Scored at
- September 28, 2026
Signal breakdown
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