Data Scientist

Stripe

H1B ✓Hybridmid levelPosted April 13, 2026

About the Role

The role involves applying statistical and machine learning models to large datasets to predict user and product performance. You will also partner with sales and product teams to design experiments and implement data science solutions at scale.

Requirements

Candidates must hold a Master's degree in a quantitative field and possess at least 3 years of relevant experience. Key requirements include proficiency in SQL, Python, R, and experience in productionalizing machine learning models.

Full Job Description

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

What you’ll do

Responsibilities

Apply statistical, time series forecasting and machine learning models on large datasets to predict future performance of users or products.
Partner closely with Sales and Data Science teams to identify important questions and answer them with data.
Design, implement and launch data science solutions using Python and R to empower data-driven decisions and products at scale.
Create analyses that generate insights for business teams.
Design, analyze, and interpret the results of experiments.

Who you are

Minimum requirements

Must have a Master's degree or foreign equivalent in Computer Science, Business Analytics, Statistics, or a related quantitative field, plus 3 years of experience in a Data Scientist or related occupation.

3 years of experience building ETL data transformation pipelines in SQL;
3 years of experience working closely with product and business teams to identify important questions and answer them with data;
2 years of experience productionalizing and implementing machine learning models;
2 years of experience productionalizing and implementing software products;
2 years of experience designing, analyzing, and interpreting the results of experiments;
2 years of experience designing, and analyzing software architectures;
2 years of experience designing, implementing, and launching data science solutions;
2 years of experience designing, implementing, and launching software solutions; and
2 years of experience applying statistical and machine learning models on large datasets to predict future performance of users or products.

Salary : $192,000 - $288,000/yr.

This salary range represents the base salary range for the role and any sales commissions/sales bonuses targets, if applicable, would be in addition to the base salary.

40 hrs/week

50% Telecommuting Permitted.

Multiple Positions Available.

Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends. WA04 #LI-DNI