Ads Strategy Lead: Data Science & Growth

Unity Technologies; Mountain View (CA); On-site; USD 244,000 - 317,000; Full time

Benefits offered by this job

Comprehensive health, life, and dental

Stock ownership

Generous vacation and personal days

Commute subsidy

Employee Resource Groups

Job summary

Unity Technologies is expanding its Data Science team for the ads business, turning large-scale data into actionable insights. You will drive analyses that reveal revenue drivers, inform supply/demand dynamics, and shape strategy across the ads ecosystem with executives.

You will collaborate with cross-functional leaders, define success metrics, and translate questions into impactful analyses while mentoring teammates and advancing ML initiatives in production.

Qualifications

• Advanced degree in Economics/CS/ML/Statistics/Math or related field.
• Strong statistical analysis and experimentation in Python, R, or equivalent, applied to large-scale data.

Responsibilities

• Lead the analysis behind Unity’s ads business: what drives revenue and growth.
• Present analysis and recommendations directly to C-level and executive leaders.
• Collaborate with PM, Engineering, Sales, and others to inform strategy.
• Transform large-scale datasets into actionable insights to support product and business success.
• Define success metrics, track performance, and measure ML/product initiatives impact.
• Guide product decisions by uncovering trends and data-driven recommendations.
• Mentor teammates and translate business questions into analytical work.

Skills

Statistical analysis

Experimentation

Python

R

Ad analytics

Education

Advanced degree in Economics/CS/ML/Statistics/Math or related field

Job description

Unity Technologies is expanding its Data Science team for the ads business, turning large-scale data into actionable insights. You will drive analyses that reveal revenue drivers, inform supply/demand dynamics, and shape strategy across the ads ecosystem with executives.

You will collaborate with cross-functional leaders, define success metrics, and translate questions into impactful analyses while mentoring teammates and advancing ML initiatives in production.