7 hours ago
Base Salary
$282k - $415k/yr
Responsibilities
- Lead the Causal ML pod across technical strategy, architecture, execution, quality, and roadmap development.
- Define and productionize a company-level causal value metric and measurement framework.
- Build reusable causal capabilities for treatment-effect estimation, surrogate validation, counterfactual policy evaluation, sensitivity analysis, and long-term outcome forecasting.
- Guide causal production applications across promotions, lifecycle interventions, ranking, recommendations, search, substitutions, demand shaping, and inventory-aware discovery.
- Connect randomized experiments, quasi-experiments, observational data, policy logs, learned models, estimation, calibration, and decision workflows.
- Set standards for validation, monitoring, reproducibility, and governance of causal estimates.
- Influence Product, Engineering, Analytics, Finance, Strategy, and business leaders through clear causal evidence and tradeoffs.
- Develop senior engineers and scientists through technical direction, design review, and coaching.
Requirements
- 10+ years of experience in causal inference, econometrics, experimentation, or causal machine learning.
- Experience leading the design and productionization of causal models, measurement platforms, experimentation systems, or large-scale decision engines.
- Deep judgment regarding randomized experiments, observational methods, surrogate endpoints, and model-based decisioning.
- Fluency with doubly robust estimation, double machine learning, instrumental variables, difference-in-differences, synthetic controls, variance reduction, heterogeneous treatment effects, contextual bandits, and off-policy evaluation.
- Strong machine learning engineering and systems ability, including data contracts, modeling pipelines, evaluation frameworks, serving patterns, and monitoring.
- Ability to reason about long-term customer and marketplace value beyond local model metrics or immediate conversion.
- Track record of influencing executives and senior cross-functional partners through technical judgment and evidence.
- Ability to create reusable abstractions, improve decision quality across teams, and raise technical standards.
Benefits
- Comprehensive benefits package including a 401(k) plan with employer matching, medical, dental, and vision benefits, disability and basic life insurance, wellness benefits, commuter benefits match, and mental health support.
- 16 weeks of paid parental leave, family-forming assistance, paid time off, paid sick leave, and 11 paid holidays.
- Equity grants are available in addition to base salary.
- For salaried roles, flexible paid time off or vacation plus 80 hours of paid sick time per year.
- The national base pay range is $282,100–$414,800 USD, localized by work location and market conditions.
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About DoorDash
DoorDash builds a marketplace and logistics platform that connects consumers with local restaurants and retailers for on-demand delivery and pickup, powered by a network of independent Dashers. It earns through delivery fees, merchant commissions, advertising, DashPass subscriptions, and white-label fulfillment via DoorDash Drive. Founded in 2013 and headquartered in San Francisco, the public company operates across the U.S. and selected international markets, and also researches automation through DoorDash Labs.