Data Scientist, Link

Stripe · Toronto · 7112 Data Science · listed August 6, 2026

Tailor your resume for this role →the original posting ↗

The shape of it

Seniority
Mid level
Experience asked
3–8 years
Where
Not stated
Requirements listed
9
Length
737 words

In the posting’s own words

Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between.

What it asks for · 9

  • PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience
  • 3+ years in Product Analytics, Experimentation and Causal Inference
  • Experience designing, running, and analyzing complex experiments or leveraging causal inference designs
  • Proficiency in SQL and Python
  • Experience in working with cross-functional teams to deliver results
  • Ability to communicate results clearly and a focus on driving impact
  • A demonstrated ability to manage and deliver on multiple projects with a high attention to detail
  • Strong business acumen and experience in synthesizing complex analyses into actionable recommendations
  • Proficiency with AI tools to accelerate model development, analysis, and coding

Also a plus

  • Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation
  • Experience deploying models in production and adjusting model thresholds to improve performance
  • A builder's mindset with a willingness to question assumptions and conventional wisdom
  • Experience with distributed tools such as Spark, Hadoop, etc.
  • A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

Degree language

  • PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience

Tools and skills named

Data
  • Experimentation3×
  • Statistics3×
  • Hadoop
  • Spark
Models & research
  • Inference4×
  • Machine learning3×
Go to market
  • Forecasting
  • Go-to-market
Languages
  • Python
  • SQL
Product & design
  • Roadmap
Ways of working
  • Cross-functional

Words the posting leans on

  • data11×
  • product9×
  • payment8×
  • experience7×
  • link7×
  • method7×
  • model6×
  • business5×
  • consumers5×
  • analytics4×
  • causal inference4×
  • data science4×
  • payment method4×
  • preferred4×
  • requirements4×
  • user4×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

The posting, your resume, and the gaps between them. One click loads all three.

Tailor your resume for this role →apply on Stripe’s board ↗

More open at Stripe

every open role at Stripe →

How this page was made

An automated read of a public job posting, fetched August 25, 2026 and last changed by Stripe on August 18, 2026. Every list above is pulled from the posting’s own sentences — nothing rewritten, nothing added, no judgment about the role or the company. Counts and seniority are read off the text by rule, so they can be wrong where the posting is unusual. The original is the only thing that binds. Openings close without warning; check the source before spending an evening on it.