Tasks:
- * Analyze results and support decisions
- * Apply causal inference to non-randomized experiments
- * Build end-to-end experimentation workflows
- * Calculate sample size and minimum detectable effect
- * Define experiment metrics
- * Design A/B testing platform and methodology
- * Design experiment hypotheses and traffic allocation
- * Detect sample ratio mismatch and allocation contamination
- * Develop statistical testing methods
- * Establish experimentation standards
- * Implement experiment trust and quality controls
- * Investigate network effects and tracking anomalies
- * Partner with product, operations, algorithm, and data teams on experiments
- * Plan platform roadmap
- * Translate business needs into platform capabilities
Perks/Benefits:
Skills/Tech stack required:
[A/B] [A/B Testing] [B testing] [Causal Inference] [CUPED] [Experimental Design] [Experiment Platform Development] [Hypothesis Testing] [Metric Design] [Minimum Detectable Effect] [Mismatch analysis] [Multiple testing] [Multiple Testing Correction] [Non Inferiority] [Non-inferiority testing] [Platform Development] [Probability and statistics] [Python] [R] [Sample Ratio Mismatch] [Sample ratio mismatch analysis] [Sample Size] [Sample Size Calculation] [Sequential testing] [Simulation] [SQL] [Statistical Analysis] [Statistical inference]
Educational requirements:
[Bachelor's Degree]
Role(s):
[Data Scientist] [Experimentation Data Scientist] [Scientist] [Senior Data Scientist]