Staff Data Scientist, Ads
Leads high-impact data science initiatives for advertising identity, measurement, experimentation, and signal quality. The role requires an advanced degree, extensive applied science or data science experience, strong statistical programming, and expertise in causal inference, experimentation, or predictive modeling.
About the job
Responsibilities
- Develop and employ probabilistic models for identity resolution, linking on-platform and off-platform actions while honoring privacy.
- Own the statistical rigor behind Brand and Conversion Lift products.
- Innovate experimental design and develop infrastructure for large-scale, low-bias advertiser testing.
- Define strategies for new signal sources, quantify their value mathematically, and incorporate them into predictive models to improve bidding efficiency and ROAS.
- Design objective functions and ground-truth sets for validating identity and measurement models.
- Collaborate with engineering, product, and sales to align strategic goals and drive execution.
- Mentor others and champion best practices in modeling, experimentation, and measurement.
Requirements
- Master's or PhD in Statistics, Mathematics, Physics, Economics, or Operations Research.
- Master's degree holders: 10+ years of industry experience in applied science or data science roles.
- PhD holders: 6+ years of industry experience in applied science or data science roles.
- Deep understanding of the advertising ecosystem.
- Expertise in measurement and experimentation at scale, identity graph creation and resolution, or predictive modeling with signal loss.
- Advanced proficiency in Python or R and SQL.
- Experience with machine learning or optimization techniques.
- Strong understanding of experimental design, causal inference, or A/B testing methodologies.
- Exceptional problem-solving and communication skills, with experience influencing product and engineering partners.
- Experience working in fast-paced, ambiguous, cross-functional environments.
Benefits
- Global benefits supporting workspace, professional development, and caregiving.
- Family planning support.
- Gender-affirming care.
- Mental health and coaching benefits.
- Comprehensive medical benefits and a health care spending account.
- Registered Retirement Savings Plan with matching contributions.
- Income replacement programs.
- Flexible vacation and paid volunteer time off.
- Generous paid parental leave.
Skills
Python, R, SQL, Machine Learning, Optimization, Experimental Design, Causal Inference, A/B Testing, Statistical Modeling, Identity Resolution, Attribution, Predictive Modeling
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