Senior ML Engineer: Ads Experimentation & Metrics

Unity; Mountain View (CA); Vor Ort; USD 149.000 - 259.000; Vollzeit

Benefits dieser Stelle

comprehensive insurance

commute subsidy

stock ownership

retirement plans

vacation

parental support

snacks

mental health programs

employee groups

assistance programs

training

volunteering support

Zusammenfassung

Unity’s Ads Experimentation Platform team seeks a senior machine learning engineer to lead validation and optimization of the global advertising ecosystem. The role involves bridging statistical methodology and large-scale engineering, with responsibilities spanning evaluation of ad delivery systems and driving product analytics.

You will design advanced statistical methodologies and build automated ML experimentation pipelines, defining surrogate LTV metrics while providing cross-functional

Qualifikationen

• 5+ years in Data Science or Applied Research in Ad Tech or marketplaces.
• Advanced degree in a quantitative field.
• Expertise in causal inference and statistics.
• Programming in Python or Scala; experience with Spark, Snowflake or BigQuery.

Aufgaben

• Evaluate ad delivery systems and drive product analytics.
• Design advanced statistical methodologies (CUPED, sequential testing, interleaving).
• Build automated ML experimentation pipelines.
• Define surrogate LTV metrics.
• Provide cross-functional leadership.
• Lead validation and optimization of the global advertising ecosystem.

Kenntnisse

Data Science

Statistics

Python/Scala

Spark

Snowflake

BigQuery

A/B Testing

Causal Inference

Ausbildung

Advanced degree in a quantitative field

Tools

Spark

Snowflake

BigQuery

Jobbeschreibung

Unity’s Ads Experimentation Platform team seeks a senior machine learning engineer to lead validation and optimization of the global advertising ecosystem. The role involves bridging statistical methodology and large-scale engineering, with responsibilities spanning evaluation of ad delivery systems and driving product analytics.

You will design advanced statistical methodologies and build automated ML experimentation pipelines, defining surrogate LTV metrics while providing cross-functional