# Staff Data Scientist, Pricing

**Company**: Block
**Location**: Bay Area, CA
**Experience**: staff
**Job type**: full-time
**Salary**: Zone A:$198,000-$297,000 USD
Zone B: $188,100-$282,100 USD
Zone C:$178,200-$267,400 USD
Zone D:$168,300-$252,500 USD
**Category**: Data Science
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/block/jobs/5364922008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_f3ab9547-23f

## Description

The Data Science team at Block turns insights from unique datasets into actions that improve the customer experience every day.

In this role, we're looking for a Data Scientist to own the modeling and experimentation at the core of how Square prices globally. You'll build the elasticity and willingness-to-pay models, design and run the pricing experiments, and stand up the analytical infrastructure that makes pricing measurable and controllable , shaping pricing strategy and deal-desk automation through the models and experiments you build.

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

Requirements:

- 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

- Prior exposure to a pricing-adjacent domain a strong plus , risk-based pricing (payments, lending, insurance), pricing science, or deal pricing analytics

- 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; experience building, testing, or evaluating LLM-powered systems in production a strong plus

## Skills

### Required
- SQL
- Python
- data visualization
- statistics
- data science
- economics
- causal inference
- experimentation
- price elasticity
- willingness-to-pay

### Nice to have
- risk-based pricing
- pricing science
- deal pricing analytics
- LLMs
- RAG systems
- agentic AI

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/block/jobs/5364922008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)