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Senior Applied Scientist Moloco Ads

💼 Full-time🗓 2026-07-26

Core

Optimizing ad auction systems and prediction infrastructure through rigorous experimentation, model refinement, and deep analysis of high-dimensional data to improve reliability, latency, and efficiency.

Role type

Senior Applied Scientist (Infrastructure & Optimization)

Builds

Online prediction and decision systems for ad auctions

Domain

Digital Advertising / Machine Learning / Systems Optimization

Deliverable

production ML models | infrastructure

Required skills

Advanced degree in CS/Mathematics, 4+ years in engineering/applied science, optimization of market prices or ML systems, analysis of high-dimensional datasets, algorithm implementation and evaluation, rigorous experimentation design, cross-functional collaboration

Preferred skills

None stated

Technologies

None explicitly named

Responsibilities

Evaluate health of internal and external system components, implement and evaluate new algorithms and features, analyze massive datasets from ad auctions and user interactions, improve reliability and latency of online prediction systems, collaborate on experiments and roadmaps

Seniority

Senior, hands-on IC

Rewrite
## About the Role The Research Science (RS) team focuses on the operation and optimization of our software systems working closely with infrastructure engineering teams, machine learning teams and data science teams. As an Applied Scientist, you will participate as an individual contributor on research projects alongside other research scientists within the context of a group of cross functional collaborators working in complex multi-causal environments to identify inefficiencies, analyze potential options, and propose solutions. Your work will contribute to driving performance improvements and cost reductions, debugging and investigating production issues, and stabilizing our core system as you develop a deep end-to-end understanding of the system. ## Responsibilities - Work with other applied scientists on projects to evaluate the health of both internal and external components to make sure the Moloco system is running safely and efficiently. - Learn from your senior peers how to identify new areas to improve our infrastructure and machine learning components by understanding internal system changes, external changes, and data changes, and identify and suggest interesting/useful next steps for your projects. - Complete task as part of larger projects to complete deep unbiased analyses. - Implement, and evaluate new algorithms and features in collaboration with senior Applied Scientists, Software Engineers and Machine Learning Engineers. - Analyze massive, high-dimensional datasets from ad auctions and user interactions to uncover insights, define success metrics, and guide modeling and product decisions. - Collaborate closely with product, engineering, and other scientists to iterate on experiments, define roadmaps, and translate business requirements into scientifically sound solutions. - Improve the reliability, latency, and efficiency of online prediction and decision systems by applying rigorous experimentation, monitoring, and continual model refinement. ## Requirements - Advanced degree in Computer Science, Mathematics or related field, or industry experience in optimization of market prices or ML systems - At least 4 years of engineering or applied science experience - Proficient verbal and written English communication skills, with the ability to contribute to the creation of presentations and reports - Quick understanding of new information and the demonstrated ability to learn new technical skills across engineering, machine learning, and data science - Track record of building positive relationships with collaborators and stakeholders and working effectively with cross-functional partners in a global company
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