# Data Scientist, Global Growth

**Company:** [Stripe](https://hotfix.jobs/companies/stripe)
**Location:** Unspecified
**Role:** Data Science
**Experience:** 8+ years
**Skills:** SQL, Python, R, Machine Learning, Statistics, Optimization, Product Analytics, Causal Inference, Experimentation, Spark, Hadoop, AI Tools
**Posted:** 2026-08-06

> The Data Scientist will partner with Global Growth teams to design experiments and optimize Stripe’s self-serve onboarding funnel. The role requires substantial data science or quantitative modeling experience, strong SQL and programming skills, and expertise in experimentation, analytics, or related quantitative methods.

## Job Description

## Responsibilities
- Partner with Global Growth teams to design and ship experiments.
- Identify improvement opportunities across stripe.com and the dashboard to help businesses worldwide get started on Stripe.
- Understand, grow, and optimize the self-serve user funnel.
- Improve the quality of the global user onboarding experience.
- Apply machine learning, statistical modeling, causal inference, optimization, experimentation, and analytics to inform company strategy, products, and user interactions.

## Requirements
- **Bachelor's degree plus 8 years**, **master's degree plus 6 years**, or **PhD plus 3 years** of data science or quantitative modeling experience.
- Proficiency in SQL and a computing language such as Python or R.
- Experience working with cross-functional teams to deliver results.
- Ability to communicate results clearly and drive impact.
- Ability to manage and deliver multiple projects with high attention to detail.
- Strong business acumen and experience synthesizing complex analyses into actionable recommendations.
- Proficiency with AI tools to accelerate model development, analysis, and coding.

## Nice-to-haves
- Hands-on experience in several of the following: machine learning, statistics, optimization, product analytics, causal inference, and experimentation.
- Experience deploying models in production and adjusting model thresholds to improve performance.
- Experience designing, running, and analyzing complex experiments or leveraging causal inference designs.
- A builder's mindset and willingness to question assumptions and conventional wisdom.
- Experience with distributed tools such as Spark and Hadoop.
- A PhD or MSc in a quantitative field such as Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, or Operations Research.

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