Prudent Technologies and Consulting
Data Scientist
New York, New York, USA · Full-time
Sponsorship not specifiedDetected 23 days ago
PythonSnowflakeDatabricksCI/CDMachine Learningscikit-learnData EngineeringData ScienceStatisticsA/B TestingProject ManagementForecastingExperimental DesignLeadershipCommunicationMentoringPublic Speaking
About the role
- Strong background in statistical modeling: regression, classification, time series forecasting, causal inference, and other techniques.
- Proficient in conducting sample size calculations, power analysis, and minimum detectable effect estimation.
Responsibilities
- Lead end-to-end A/B testing initiatives and Geo Experiments, from hypothesis formation and experimental design to statistical analysis and business recommendations
- Partner with stakeholders to identify optimization opportunities and translate complex analytical findings into clear business recommendations
Requirements
- Bachelors in Statistics, Economics, Computer Science, Engineering, Mathematics, Physics, or a related field + 7 years of experience with an emphasis on experimentation or causal inference.
- Robust knowledge of causal inference approaches such as propensity scores, synthetic controls, difference-in-differences, doubly robust methods, meta learners, and uplift modeling.
- Experience managing multiple testing scenarios and controlling false discovery rates.
- Ability to deploy both Bayesian and frequentist statistical approaches.
- Deep understanding of assumptions required for causal inferences, including the foundational statistical concepts that underpin the approaches.
- MS in computer science, statistics, math or a related quantitative field 10+ years of relevant experience OR PhD + 3 years of relevant experience with an emphasis on experimentation or causal inference.
- Experience with ETL and data engineering: data extraction, transformation, integration, and quality controls for analytics at scale.
- Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, and Github.
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