Data Scientist, Performance Analytics within Engineering

PubMatic
United States
19 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Artificial Intelligence Big Data BigQuery Software Quality Cursor Software Debugging Python (Programming Language) Machine Learning Standard Sql SQL Databases GitHub Copilot
+6 more
Snowflake Apache Spark Generative AI GPT Data Pipelines Databricks

Job description

We are looking for a Data Scientist, Performance Analytics within Engineering to build performance intelligence for our advertising platform. The role will analyze campaign and platform performance, identify anomalies and opportunities, investigate root causes, and translate data into actions for Engineering, Trading, Product, and Business. This is not primarily a reporting role-the focus is understanding what is happening, why, and what we should do about it.

What You’ll Do

  • Analyze performance across campaigns, inventory, audiences, bidding, models, and conversions.
  • Monitor and investigate CPA, CPC, CTR, VCR, ROAS, spend, delivery, and revenue.
  • Proactively detect performance anomalies and optimization opportunities.
  • Perform root-cause analysis across models, inventory, identity, attribution, audience, and data quality.
  • Design and analyze A/B tests and experiments.
  • Build reusable SQL/Python analyses, metrics, and automated diagnostics.
  • Partner with Engineering and Trading to turn insights into measurable improvements.
  • Convert recurring investigations into AI-assisted troubleshooting and automation., We value engineers who actively leverage Generative AI tools and IDEs (e.g. GitHub Copilot, ChatGPT, Claude, Cursor, Windsurf etc.) to accelerate development, improve code quality, automate repetitive tasks, and enhance documentation and debugging workflows. Engineers who demonstrate AI-first thinking using these tools to drive faster experimentation, ideation, and technical execution will thrive in our high-scale, performance-critical environment.

Requirements

  • Strong SQL and Python skills with experience analyzing large-scale datasets.
  • Strong analytical, statistical, and experimentation fundamentals.
  • Experience with platforms such as Snowflake, Spark, Trino, Databricks, or BigQuery.
  • Understanding of data pipelines, data modeling, and data quality.
  • Strong problem-solving and communication skills.
  • AdTech, marketplace, recommendation, or high-scale platform experience preferred.
  • Experience with RTB, bidding, attribution, campaign optimization, or ML-driven systems is a strong plus., * Bachelor’s degree in Engineering (CS/IT) or an equivalent degree from a well-known institute or university; advanced degree is a plus but not required given depth of experience.

About the company

Return to Office: PubMatic employees throughout the global have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions.

Benefits: Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more!

Diversity and Inclusion: PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

About PubMatic

PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes.

Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

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