Senior Applied Scientist (all genders)
Tasks
- Apply quasi experimental methods
- Build KPI frameworks for evaluation
- Communicate findings uncertainty trade offs
- Define best practices for experimentation and causal inference
- Define hypotheses estimands guardrails success metrics
- Design observational studies to estimate incremental effects
- Develop machine learning and econometric models
- Lead impact measurement for products and initiatives
- Own experimentation charter
- Select causal design randomized experiments
- Support peer reviews mentor colleagues
- Translate evidence into product decisions
Perks/Benefits
- Discounts from external partners
- Employee shares program
- Family support services
- Mental health support
- Paid vacation
- Paid volunteering days
- Peer-to-peer review
- Relocation assistance
- Training platform
- Wellbeing benefits
Skills/Tech-stack
Causal Inference | Causal Machine Learning | Databricks | Doubly Robust | Doubly Robust Methods | Econometrics | Experimental Methods | KPI frameworks | Machine Learning | Optimization | Panel data | Python | Quasi Experimental | Quasi-experimental methods | Randomized experiments | SQL | Spark | Unconfoundedness
Education
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