Staff Data Scientist, Pricing
Own modeling and experimentation for global pricing, including price elasticity and willingness-to-pay models, pricing experiments, analytical infrastructure, AI system evaluation, ETL datasets, dashboards, causal impact measurement, and stakeholder recommendations.
Responsibilities
- Model price elasticity and willingness-to-pay across segments, geographies, and payment methods.
- Design, run, and interpret pricing experiments, including A/B, difference-in-differences, and bandit-based tests.
- Analyze merchant economics across interchange, scheme, and risk-cost layers.
- Build pricing intelligence for rate recommendations, ROI logic, pre-approval logic, guardrails, and mispricing detection.
- Evaluate AI systems for accuracy, edge cases, bias, drift, and mispricing.
- Own analysis, pipelines, ETL, experimentation, and visualization.
- Build pricing analytics dashboards and curated datasets.
- Measure the impact of AI-driven pricing automation using causal methods.
- Process, cleanse, and combine data sources into curated ETL datasets.
- Partner with Finance, Risk, Product, and go-to-market stakeholders.
Requirements
- Bachelor's degree in statistics, data science, economics, or a similar STEM field with 7+ years of relevant experience, or a graduate degree with 5+ years of relevant experience.
- Causal inference and experimentation experience, including price elasticity or willingness-to-pay modeling.
- Advanced SQL and data visualization skills with tools such as Tableau or Looker.
- Python or R experience for scripting, data analysis, and AI system evaluation.
- Strong cohort and funnel analysis experience and knowledge of statistical concepts.
- Working understanding of generative AI architectures, including LLMs, RAG systems, and agentic AI.
- Pricing-adjacent experience in risk-based pricing, pricing science, or deal pricing analytics is a plus.
Benefits
- Remote work
- Medical insurance
- Flexible time off
- Retirement savings plans
- Modern family planning