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# Data Scientist, Mobile App Performance

- **Company:** PubMatic
- **Location:** Redwood City, United States (Remote available)
- **Experience:** Expert
- **Salary:** $225,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Big Data, Apache Hadoop, Apache Hive, Statistical Hypothesis Testing, Mobile Application Software, Python (Programming Language), Machine Learning, SQL Databases, Boosted Trees, Apache Spark, Deep Learning, Information Technology, K Means
- **Published:** October 10, 2026
- **Apply:** https://www.dice.com/job-detail/05edde98-5ee4-4ab3-b0af-a5bfafd2e927

## About the Role

* 5+ years of hands-on data science experience, with a focus on ML model development, statistical inference, and production-grade analysis

 * Deep fluency in Python and SQL; experience with large-scale data environments (Spark, Hadoop, Hive, or equivalent)

 * Strong foundation in experimental design, hypothesis testing, regression modeling, and causal inference

 * Experience with ML algorithms relevant to ranking, prediction, and optimization problems: gradient boosted trees, deep learning, k-means, and related methods

 * Proven ability to extract actionable signals from noisy, high-volume datasets and communicate findings clearly

 * Track record of owning projects end-to-end, from problem framing through to production impact

Strongly Preferred

 * Experience in mobile advertising, programmatic, or ad tech

 * Familiarity with mobile measurement and attribution or campaign performance optimization in mobile applications

 * Background working alongside ML engineering or product teams on systems where the model is the product

 * Advanced degree (Master's or PhD) in Statistics, Computer Science, Mathematics, or a related quantitative discipline

## Description

Own the data science function for Mobile App performance, working at the intersection of ML and programmatic advertising. This is a high-ownership, high-visibility role--both internally and with our customers.

What You'll Do:

Model Development

 * Build signal enrichment pipelines leveraging contextual signals, behavioral data, and mobile attribution frameworks

 * Develop production-grade predictive models based on event data (clicks, installs, in-app events, retention).

 * Partner with GTM teams to translate metric frameworks into buyer-facing insights and predictive models

Drive Product Development

 * Conduct deep-dive analysis to influence product and engineering decisions: pull and query large datasets, extract valuable signals from noise, and produce actionable insights into how we can drive better outcomes for buyers and publishers

 * Develop predictive modeling frameworks to quantify performance gains from product hypotheses before they ship - reducing decision latency and de-risking the roadmap

 * Act as the senior data science voice in product discussions. Bring partner-level insight and analytical rigor to roadmap decisions.

Evaluate and Improve System Health

 * Understand changes and drivers across PubMatic's mobile ecosystem: diagnose issues, identify structural inefficiencies, and track input/output metrics at each system component

 * Work with product and engineering to define success metrics, design experiments, and evaluate new features before and after launch.

 * Design experiment frameworks and causal inference methods that produce reliable, unbiased signals for product and business decisions