Staff Data Scientist, Ads Experimentation

Posted 6 days agoViewed

💎 Seniority level: Staff, 6+ years

📍 Location: United States

💸 Salary: 217000.0 - 303900.0 USD per year

🔍 Industry: Digital Advertising

🏢 Company: Reddit👥 1001-5000💰 $410,000,000 Series F over 3 years ago🫂 Last layoff almost 2 years agoNews Content Social Network Social Media

🗣️ Languages: English

⏳ Experience: 6+ years

🪄 Skills: AWSPythonSQLApache AirflowData AnalysisHadoopMachine LearningNumpyCross-functional Team LeadershipProduct DevelopmentAlgorithmsData engineeringData scienceRegression testingPandasSparkCommunication SkillsAnalytical SkillsMentoringData visualizationData modelingA/B testing

Requirements:

M.S.: 10+ years of industry data science experience, emphasizing experimentation and causal inference.
Ph.D.: 6+ years of industry data science experience, emphasizing experimentation and causal inference
Master's or Ph.D. in Statistics, Economics, Computer Science, or a related quantitative field
Expertise in experimental design, A/B testing, and causal inference
Proficiency in statistical programming (Python/R) and SQL
Demonstrated ability to apply statistical principles of experimentation (hypothesis testing, p-values, etc.)
Experience with large-scale data analysis and manipulation
Strong technical communication skills for both technical and non-technical audiences
Ability to thrive in fast-paced, ambiguous environments and drive action
Desire to mentor and elevate data science practices
Experience with digital advertising and marketplace dynamics (preferred)
Experience with advertising technology (preferred)

Responsibilities:

Lead the design, implementation, and analysis of sophisticated A/B tests and experiments, leveraging innovative techniques like Bayesian approaches and causal inference to optimize complex ad strategies
Extract critical insights through in-depth analysis, developing automated tools and actionable recommendations to drive impactful decisions Define and refine key metrics to empower product teams with a deeper understanding of feature performance
Partner with product and engineering to shape experiment roadmaps and drive data-informed product development
Provide technical leadership, mentor junior data scientists, and establish best practices for experimentation
Drive impactful results by collaborating effectively with product, engineering, sales, and marketing teams

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