Data Scientist
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.
What this role actually needs.
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. 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. - Build ETL data transformation pipelines in SQL. Requirements: - 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; Company context: Stripe builds financial infrastructure for internet businesses, with strong hiring across platform, product, data, and AI-adjacent teams.
Day-to-day expectations
Stripe lists these responsibilities for the Data Scientist role.
- 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.
- Build ETL data transformation pipelines in SQL.
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- 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;
Why this listing is more than a copied job post.
Data Scientist is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
United States tech market
United States roles on UpJobz are filtered for high-tech relevance, source freshness, and actionable employer detail before they are allowed into SEO surfaces.
Compensation read
The employer source does not expose a reliable salary range, so candidates should ask for compensation early instead of waiting until late-stage interviews.
Work authorization read
Current extracted signal: United States residents. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.
Location read
Because this is remote, country scope and time-zone expectations matter as much as the title. Confirm the employer's allowed work locations on stripe.com.
Browse similar jobs
Turn this listing into an application plan.
This is the first pass at the premium UpJobz layer: a fast brief that helps serious applicants move with more clarity.
Next moves
- Tailor your resume around machine-learning and python instead of sending a generic application.
- Use the first two bullets of your application to connect your background directly to data scientist is a high-signal on-site role in remote (united states), and it is most realistic for united states residents.
- Open the role quickly if it fits and bookmark three similar jobs before you leave the page.
Interview themes
Watchouts
- Compensation is hidden, so get range clarity in the first recruiter conversation.
- Use united states residents as part of your positioning so the recruiter does not have to infer it.
- Lead with distributed collaboration, async delivery, and timezone discipline.
Keywords to match against your background
Use these terms to decide whether your resume, portfolio, and recent projects line up with the role.
Apply through the employer source
Open the source listing from stripe.com, confirm the role is still active, then apply on the employer or ATS page.
Source: stripe.com · Source ID: 7809414 · Confidence: 94/100 · Last checked: May 7, 2026
How UpJobz verifies job sourcesContinue browsing tech jobs