Staff Data Scientist - Ads
US remote-friendlyFull-TimeStaff
Salary217000 - 303900 USD per year
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Job Details
- Experience
- For M.S. holders: 10+ years of industry experience in applied science or data science roles, For Ph.D. holders: 6+ years of industry experience in applied science or data science roles
- Required Skills
- PythonSQLMachine LearningA/B testingR
Requirements
- Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research
- 10+ years of industry experience in applied science or data science roles (for M.S. holders)
- 6+ years of industry experience in applied science or data science roles (for Ph.D. holders)
- Deep understanding of the ads ecosystem
- Demonstrated expertise in Measurement & Experimentation at Scale (with focus on lift and attribution)
- Demonstrated expertise in Identity Graph Creation & Resolution Methodology and Infrastructure
- Demonstrated expertise in Predictive Modeling with Signal Loss
- Advanced proficiency in statistical programming (Python or R)
- Advanced proficiency in 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 a track record of influencing product and engineering partners
- Experience working in fast-paced, ambiguous environments with cross-functional teams
Responsibilities
- Develop/employ probabilistic models for identity resolution and design methodologies linking on-platform and off-platform actions to maximize addressability while honoring privacy.
- Own the statistical rigor behind Reddit’s Brand and Conversion Lift products, innovating experimental design and developing infrastructure for large-scale, high-velocity, low-bias testing.
- Define the strategy for new signal sources, mathematically quantify their value, and work with modeling teams to incorporate them into predictive models.
- Design objective functions and truth sets to train models and measure the incremental impact of the identity graph, solving challenges in validating identity and measurement.
- Collaborate deeply with engineering, product, and sales to align on strategic goals, translate insights into action, and drive execution.
- Set a high technical bar by mentoring others and championing best practices across modeling, experimentation, and measurement.
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