Principal Data Scientist
Ibotta
full-time
Posted on:
Location Type: Hybrid
Location: Denver • Arizona, California, Florida, Illinois, Iowa, Kansas, Maryland, Massachusetts, Minnesota, Missouri, Montana, Nevada, New Jersey, New York, North Carolina, Ohio, Oklahoma, Pennsylvania, Tennessee, Texas, Utah, Virginia, Washington, Wisconsin • 🇺🇸 United States
Visit company websiteSalary
💰 $180,000 - $200,000 per year
Job Level
Lead
Tech Stack
AWSAzureCloudGoogle Cloud PlatformPySparkPythonSparkSQL
About the role
- 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
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.
Benefits
- Competitive pay
- Flexible time off
- Benefits package (including medical, dental, vision)
- Lifestyle Spending Account
- Employee Stock Purchase Program
- 401k match
- Paid parking
- Snacks
- Occasional meals
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data sciencemachine learningadvanced analyticsSQLPythondistributed computingSparkPySparkMLOpsexperimental methods
Soft skills
collaborative problem-solvingmentoringcommunicationpresentation skillspartnership buildingtranslating technical conceptscode qualityleadershipcoachingtraining program development
Certifications
Bachelor's degreeMaster's degreePh.D.