Note: The job is a remote job and is open to candidates in USA. Block is a technology company focused on increasing access to the global economy. They are seeking a Staff Data Scientist to own modeling and experimentation for pricing strategies, leveraging unique datasets to improve customer experiences and shape pricing strategies.
Responsibilities
- Model price elasticity and willingness-to-pay across segments, geographies, and payment methods, and quantify the trade-off between margin, conversion, and merchant retention
- Design, run, and read out pricing experiments (A/B, difference-in-differences, and bandit-based dynamic tests) and translate results into recommendations that shape strategy
- Decompose merchant economics across interchange, scheme, and risk-cost layers to identify where pricing can flex and where it can't
- Build the pricing intelligence that powers Square's agentic deal tooling (DealBot) — rate recommendations, ROI and pre-approval logic, guardrail configurations, and mispricing detection — so quotes are fast, accurate, and within guardrails at scale
- Evaluate and monitor the AI systems you ship — pre-deployment testing for accuracy, boundary and edge cases, and bias in rate recommendations, and in-production monitoring for accuracy, drift, and mispricing — so agentic pricing tools stay reliable as the business changes
- Own end-to-end execution across the stack — analysis, pipeline, ETL, experimentation, and visualization
- Approach problems from first principles, using a variety of statistical and modeling techniques to understand customer behavior and price response
- Build and maintain the pricing analytics the team relies on — price realization, margin leakage, discount-waterfall, and win/loss analyses — as self-serve dashboards and curated datasets
- Measure the impact of AI-driven pricing automation with causal methods (interrupted time series, difference-in-differences) on deal velocity, quote acceptance, and margin
- Write code to process, cleanse, and combine data sources into curated ETL datasets easily used by the broader team
- Partner closely with cross-functional stakeholders across Finance, Risk, Product, and go-to-market teams, translating complex technical and AI concepts clearly for non-technical audiences
Skills
- A bachelor degree in statistics, data science, economics, or similar STEM field with 7+ years of experience in a relevant role OR a graduate degree in statistics, data science, economics, or similar STEM field with 5+ years of experience in a relevant role
- Fluency in causal inference and experimentation, with hands-on experience modeling price elasticity or willingness-to-pay
- Advanced proficiency with SQL and data visualization tools (e.g. Tableau, Looker, etc)
- Experience with scripting and data analysis programming languages, such as Python or R, including using them to evaluate AI system behavior
- Gone deep with cohort and funnel analyses, with a solid understanding of statistical concepts such as selection bias, probability distributions, and conditional probabilities
- Comfort leveraging AI tools to accelerate modeling and analysis, and a working understanding of generative AI architectures — LLMs, RAG systems, and agentic AI
- Prior exposure to a pricing-adjacent domain a strong plus — risk-based pricing (payments, lending, insurance), pricing science, or deal pricing analytics
- Experience building, testing, or evaluating LLM-powered systems in production a strong plus
Benefits
- Remote work
- Medical insurance
- Flexible time off
- Retirement savings plans
- Modern family planning
Company Overview
Company H1B Sponsorship