Principal Data Scientist, Causal Inference

Role Overview

• Help lead the continued evolution of Ibotta's measurement methodology through exploration of cutting-edge measurement research and experimental design
• Collaborate as the go-to troubleshooter for measurement anomalies—exploring outlier results, diagnosing data quality issues, and validating statistical assumptions across alpha, beta, and production measurement systems
• Lead code reviews and architecture discussions, providing expert guidance on design patterns, scalability, and technical trade-offs
• Foster a culture of code quality, rigorous measurement, and collaborative problem-solving
• Evaluate and adopt new tools, explore frameworks and innovative model forms that enhance team effectiveness, while maintaining code quality standards
• Lead enterprise-wide data science initiatives spanning 6+ months with measurable business impact across multiple teams and KRs
• Build trusted partnerships with C-suite executives, product managers, and data science leaders to translate business problems into technical solutions while delivering with consistency and transparency
• Present complex technical concepts clearly to both technical and non-technical audiences, including executive leadership
• Deliver high impact presentations on key initiatives and research, with easily understood visualizations, to drive insight and adoption
• Mentor more junior data scientists through technical guidance, code reviews, and strategic coaching
• Create technical training programs and documentation that elevate organizational data science maturity
• Embrace and uphold Ibotta's Core Values: Integrity, Boldness, Ownership, Teamwork, Transparency, & A good idea can come from anywhere

Requirements

• 10+ years of professional experience in data science, machine learning, or advanced analytics with demonstrated transformational impact
• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Data Science, or related quantitative field required; Master's or Ph.D. strongly preferred
• Experience in performance marketing, retail media, e-commerce, or CPG analytics environments strongly preferred
• Expert-level SQL and Python with demonstrated ability to write clean, maintainable, well-tested production-grade code
• Experience with distributed computing (Spark, PySpark) and cloud platforms (AWS, GCP, Azure) is a requirement
• Strong software engineering practices: version control (Git), CI/CD, unit testing, code review, design patterns
• Advanced ML frameworks and techniques (time series, ensemble methods) and MLOps practices (model deployment, monitoring, feature engineering) strongly preferred
• Deep expertise in experimental methods like RCTs and AB testing at scale, along with quasi-experimental designs: difference-in-differences, propensity score matching, regression discontinuity, and similar modalities
• Deep understanding of performance marketing metrics (ROAS, incrementality, new-to-brand acquisition)​, and ability to quantify and communicate business impact

Tech Stack

• AWS
• Azure
• Cloud
• Google Cloud Platform
• PySpark
• Python
• Spark
• SQL

Benefits

• competitive pay
• flexible time off
• benefits package (including medical, dental, vision)
• Employee Stock Purchase Program
• 401k match
• Denver office perks include paid parking, snacks, and occasional meals