Data Scientist – Experimentation & Causal Inference
Tasks
- Analyze observational data
- Apply statistical methods for causal inference
- Design and implement randomized controlled trials
- Design causal models
- Estimate causal impact of experiments
- Maintain documentation of models and experiments
- Prepare reports for non-technical audiences
- Validate experimental design and assumptions
Perks/Benefits
- Collaborative culture
- Flexible work culture
- Global opportunities
- High-impact environment
- Professional development
- Vibrant community
Skills/Tech-stack
Azure | Azure DevOps | Causal Discovery | Causal Forest | Causal Inference | Causal Models | CausalImpact | CausalML | DAG | DID | Databricks | Difference-in-differences | DoWhy | Double Machine Learning | EconML | Fixest | Gsynth | Heterogeneity Analysis | Machine Learning | MatchIt | Multiple Testing Control | Multiple testing | Omitted Variable Bias | Parallel Trends | Potential Outcomes | Power analysis | PySpark | Python | R | Randomized-Controlled Trials | SQL | SUTVA | Sample Size | Sample Size Calculation | Scikit-learn | Selection bias | Spillovers | Staggered Difference in Differences | Statistical Power | Statistical power analysis | StatsModels | Synth | Synthetic control
Education
N/A
Roles
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