AdTechTalent
Data Science20 days agoOn-site

Unity

Senior Machine Learning Engineer, Ads Experimentation & Measurements

machine learningcausal inferenceexperimental designad techdata sciencepythonscalasparksnowflakebigquerycupedinterleavingswitchback testingA/B testingstatistical methodologieslong-term valueLTVautomated pipelines

Key details

Salary

Not specified

Employment type

Full-time

Seniority

Senior

Years experience

5-10

Location

New York, US

Full job description

Unity’s Ads Experimentation Platform team seeks a senior machine learning engineer to lead the validation and optimization of the global advertising ecosystem. The role involves technical leadership on experimentation and evaluation, bridging statistical methodology and large-scale engineering. Responsibilities include evaluating ad delivery systems, driving product analytics, designing advanced statistical methodologies (CUPED, sequential testing, interleaving), building automated ML experimentation pipelines, defining long-term value proxy metrics, and providing cross-functional leadership. Requirements include 5+ years in Data Science or Applied Research in Ad Tech or marketplaces, MS or PhD in a quantitative field, expertise in causal inference and statistics, programming skills in Python or Scala, experience with Spark, Snowflake, or BigQuery, and practical experience with advanced testing methodologies. Benefits include health insurance, commute subsidy, stock ownership, retirement plans, vacation, parental support, snacks, mental health programs, employee resource groups, assistance programs, training, and volunteering support. Location: New York, NY, USA. Salary range: $148,700 to $229,900 USD.

What you'll do

  • Evaluate pacing and ad selection systems with strong domain knowledge of the ads ecosystem
  • Drive product decisions through analytics by defining metrics, building measurement frameworks, analyzing A/B test results, and translating experiment outcomes into actionable insights
  • Design statistical methodologies for the experimentation platform including variance reduction (CUPED), sequential testing, and interleaving frameworks
  • Build statistical foundations for automated pipelines that autonomously test and select optimal features and hyperparameters at scale
  • Research and validate surrogate metrics that correlate with long-term user retention, churn, and value
  • Serve as the lead subject matter expert on experimentation for ML, Product, and Engineering teams ensuring statistical rigor throughout the product lifecycle

Requirements

  • 5+ years of experience in Data Science or Applied Research, specifically within Ad Tech, Marketplaces, or high-scale experimentation platforms
  • MS or PhD in a quantitative field (Statistics, Economics, Computer Science, Operations Research, or equivalent)
  • Deep expertise in causal inference, experimental design, and frequentist/Bayesian statistics
  • Strong programming skills in Python or Scala
  • Experience with large-scale data processing frameworks like Spark, Snowflake, or BigQuery
  • Practical experience implementing advanced testing methodologies like CUPED, interleaving, or switchback testing in production environments
  • Ability to translate complex statistical concepts into clear product roadmaps and mentor engineering teams on experimental rigor

Tech stack

PythonScalaSparkSnowflakeBigQueryCUPEDinterleavingswitchback testing

Benefits

Comprehensive health, life, and disability insuranceCommute subsidyEmployee stock ownershipCompetitive retirement/pension plansGenerous vacation and personal daysSupport for new parents through leave and family-care programsOffice food snacksMental Health and Wellbeing programs and supportEmployee Resource GroupsGlobal Employee Assistance ProgramTraining and development programsVolunteering and donation matching program

Apply now

This MVP uses a placeholder application flow. In production, this section can connect to an external apply URL or a native application form.

Continue to applicationBrowse more jobs

Similar jobs

More roles worth a look

Related opportunities based on specialty and working model so candidates can keep momentum.