Principal Data Scientist, Ads Measurement & Causality

Walmart Global Tech; Bellevue (WA); On-site; USD 132,000 - 264,000; Full time

Benefits offered by this job

Stock

Company-paid life insurance

Paid time off

Job summary

Walmart Global Tech in Bellevue, WA is seeking a Principal Data Scientist to lead the design and development of Walmart Connect's ads incrementality measurement platform, with a focus on causal inference and RCT experimentation.

You will own the methodology end-to-end, partner with engineering and product to push solutions into production, and mentor senior scientists while setting the bar for rigorous, causally grounded measurement at scale.

Qualifications

• PhD or Master's in a quantitative field is required or strongly preferred.
• 5+ years in data science or quantitative research, ads industry preferred.
• Deep expertise in causal inference and incrementality-based optimization.

Responsibilities

• Design and implement large-scale causal inference methods to measure incremental lift across campaigns.
• Establish evaluation frameworks and solution readiness standards for causal methods.
• Author technical designs and present to senior leadership.
• Define science roadmap for incrementality and causal measurement.
• Develop event-grain incrementality models to power ads bidding decisions.
• Mentor senior and mid-level scientists.

Skills

Causal inference

Incrementality

Experiment design

Python

SQL

Education

PhD in Statistics, Economics, Econometrics, Computer Science or related field

Master's in Statistics, Economics, Econometrics, Computer Science or related field

Tools

Spark

BigQuery

Python

SQL

Job description

Walmart Global Tech in Bellevue, WA is seeking a Principal Data Scientist to lead the design and development of Walmart Connect's ads incrementality measurement platform, with a focus on causal inference and RCT experimentation.

You will own the methodology end-to-end, partner with engineering and product to push solutions into production, and mentor senior scientists while setting the bar for rigorous, causally grounded measurement at scale.