Data Scientist II at LexisNexis applying statistical analysis and building predictive models for fraud and credit risk. Collaborating with teams to enhance existing products and provide actionable insights.
About the role
- Principal Data Scientist leading marketing analytics initiatives at Ibotta. Collaborating across teams to enhance measurement solutions and drive business impact through data science.
Responsibilities
- 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
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