Staff Data Scientist Pricing
You will own modeling and experimentation for global pricing. You will build price elasticity and willingness-to-pay models, design pricing experiments, develop analytical infrastructure, evaluate AI pricing systems, create ETL datasets and dashboards, measure automation impact, and translate technical findings into recommendations for Finance, Risk, Product, and go-to-market stakeholders.
Responsibilities
- Model price elasticity and willingness-to-pay across segments, geographies, and payment methods
- Design, run, and interpret pricing experiments
- 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
- Price elasticity or willingness-to-pay modeling
- Advanced SQL
- Data visualization tools such as Tableau or Looker
- Python or R
- Cohort and funnel analysis
- Statistical concepts including selection bias, probability distributions, and conditional probabilities
- Generative AI architectures including LLMs, RAG systems, and agentic AI
Benefits
- Remote work
- Medical insurance
- Flexible time off
- Retirement savings plans
- Modern family planning