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