Data Scientist, Fraud
Stripe
Data Scientist, Fraud at Stripe is a full time role based in Toronto, Ontario, Canada. It was published on 6 August 2026 and was open at last check.
| Role | Data Scientist, Fraud |
|---|---|
| Company | Stripe |
| Location | Toronto, Ontario, Canada |
| Employment type | Full Time |
| Published | 6 August 2026 |
| Status | Open at last check |
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.
About the team
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 Fraud, Losses, and Financial Crime Data Science team builds the models and data products that protect Stripe and its users from fraud, account takeover, and financial crime. We own the full fraud and loss modeling stack - from account takeover detection and card fraud classification to merchant-level loss estimation, unsupervised anomaly detection, and financial crime risk modeling. We partner with Fraud Engineering, Financial Crimes Engineering, and Risk Operations to bring these systems into production and ensure they have measurable impact on Stripe's financial integrity and user trust.
What you'll do
We're looking for a Data Scientist to join the Fraud Data Science team. In this role, you'll build and improve the models that power Stripe's fraud detection and loss management systems. You'll work closely with Fraud Engineering and Risk Operations to move models from research to production, and you'll use data to surface insights that shape fraud strategy across the business.
Data scientists on this team apply supervised and unsupervised machine learning, statistical modeling, causal inference, optimization, and experimentation to some of the most consequential risk problems in global payments.
Who you are
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
- PhD with 1-3 years, MS or MA with 2-6 years, or BS or BA with 4-8 years of data science or quantitative modeling experience
- Experience with Fraud, Risk or Financial Crimes
- Proficiency in SQL and a computing language such as Python or R
- 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
Preferred qualifications
- Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, 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 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)
Create your free OnJob profile to apply — we'll take you to Stripe's application after sign-up. · Posted 6 Aug 2026.
Data Scientist, Fraud at Stripe — questions answered
What does the Data Scientist, Fraud role at Stripe pay?
Stripe does not publish a salary on this Data Scientist, Fraud listing, so OnJob shows no figure for it rather than an estimate. For what this role pays across the market, the OnJob salary guides aggregate the live listings that do disclose pay.
Where is the Data Scientist, Fraud role at Stripe based?
Stripe lists this Data Scientist, Fraud role in Toronto, Ontario, Canada, advertised as full time work at that location. Larger employers sometimes cover several sites under one city name, so confirm the exact office with Stripe before you apply.
Is the Data Scientist, Fraud role at Stripe still open?
The Data Scientist, Fraud posting at Stripe was open at OnJob's last check of the employer's careers page, having been published on 6 August 2026. OnJob re-checks source listings on each build and marks a role closed once it disappears, but listings can close without notice, so the employer's own page is the final word.
How do you apply for the Data Scientist, Fraud role at Stripe?
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