Staff Software Engineer, Experimentation & Data Systems

Blue Line Search Group; San Francisco (CA); On-site; USD 194,000 - 285,000; Full time

Benefits offered by this job

401(k) plan with employer matching

16 weeks of paid parental leave

wellness benefits

commuter benefits match

paid time off and paid sick leave

medical, dental, and vision benefits

11 paid holidays

disability and basic life insurance

family-forming assistance

a mental health program

Job summary

DoorDash is seeking a Staff Applied Scientist to lead the scientific direction for Curie and the Decision Systems Experimentation Platform.

You will define statistical, causal inference, machine learning, and AI capabilities that empower faster, more trustworthy decisions across the company, partnering with engineers, data scientists, product managers, and operators to translate advanced methods into reliable platform capabilities.

Qualifications

• 6+ years of industry experience or equivalent applied research in statistical, causal inference, ML, or experimentation systems with measurable business impact.
• Deep expertise in experimentation and causal inference, with production experience in variance reduction, ratio metrics, sequential testing, heterogeneous treatment effects, marketplace interference, or quasi-experimental designs.
• Strong coding and data skills, including production data pipelines and reviewing complex analytical SQL for statistical correctness.
• Experience translating statistical or machine learning methods into reliable, scalable platform capabilities in collaboration with engineering and product teams.

Responsibilities

• Define and advance the statistical, causal inference, machine learning, and AI capabilities that power high-quality decision-making across DoorDash.
• Own the statistical contract for experiment analysis, including metrics, populations, exposure windows, covariates, edge cases, and rule definitions.
• Review analytical SQL and validate statistical parity to ensure correctness across engine migrations and production systems.
• Mentor data scientists, product teams, and engineers on experimental design, metric strategy, and interpretation of results.

Skills

Experimentation

Causal inference

Machine learning

Statistical methods

SQL

Python

Mentoring

Communication

Tools

Python

SQL

Job description

DoorDash is seeking a Staff Applied Scientist to lead the scientific direction for Curie and the Decision Systems Experimentation Platform.

You will define statistical, causal inference, machine learning, and AI capabilities that empower faster, more trustworthy decisions across the company, partnering with engineers, data scientists, product managers, and operators to translate advanced methods into reliable platform capabilities.