Posted 3 months ago
Data Scientist, Fraud
@ Stripe
Toronto, Ontario
Overview
Stripe is hiring a Data Scientist for its Fraud Data Science team to build and improve models that detect fraud and manage losses in global payments. The role works with Fraud Engineering and Risk Operations to move models into production. Minimum requirements include 2 to 8 years of data science experience depending on degree, plus SQL and Python or R.
Responsibilities:
- Build and improve fraud detection and loss management models
- Move models from research to production with Fraud Engineering
- Work with Risk Operations on fraud strategy
- Surface insights that shape fraud strategy across the business
Requirements summary:
- 2 to 8 years of data science or quantitative modeling experience, depending on degree
- Experience with fraud, risk or financial crimes
- Proficiency in SQL and Python or R
- Ability to communicate results clearly and drive impact
Tools & skills
Source and dates
Employer career site / ATS feed · greenhouse
- Employer posting date
- 2026-08-06
- First seen by our source
- 2026-10-10
- Source record updated
- 2026-10-29
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Department | Data & analytics |
| Experience | 2+ years |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Bachelor’s degree (required), Master’s degree (preferred), Doctorate (preferred) |
| Fields of study | Statistics, Engineering, Mathematics, Economics, Quantitative Finance |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Stripe
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Help increase the GDP of the internet.
Full company description
Stripe builds programmable financial services. 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. Headquartered in San Francisco and Dublin, the company aims to increase the GDP of the internet.
- LinkedIn followers
- 1,286,676
- People associated on LinkedIn
- 14,284
- Reported office locations
- 354 Oyster Point Blvd, South San Francisco, California 94080, US
- 1 Wilton Park, Wilton Terrace, Dublin, County Dublin D02 FX04, IE
- 920 5th Ave, Seattle, Washington 98104, US
- 201 Bishopsgate, London, England EC2M 3NS, GB
- 10, Boulevard Haussmann, Paris, Ile-de-France 75009, FR
- 89 Neil Rd, Central Business District, Singapore 088894, SG
- 1-5-8 Jingumae, Tokyo, Shibuya-ku 150-0001, JP
- 515 N State St, Chicago, Illinois 60610, US
- 28 Liberty Street, New York, NY 10005, US
- Singel 542, Amsterdam, North Holland 1017, NL
- Avenida Paseo de la Reforma 296, Ciudad de Mexico, Colonia Juarez 06600, MX
- 222 Exhibition St, Melbourne, Victoria 3000, AU
- Avenida Paulista 1374, Paulínia, São Paulo 13140-000, BR
- Church Street Haridevpur, Shanthala Nagar, Ashok Nagar, Bengaluru, Karnataka 560001, IN
- Business categories
- Finance
- InsurTech
- SaaS
- FinTech
- Financial Services
- Venture Capital
- Mobile Payments
- Other recorded names
- Stripe
- Profile identifies a recruitment agency
- No
- Reported total investment
- 9,440,247,725
Currency and observation date were not supplied; this is not a current valuation or a funding round.
Stripe builds programmable financial services. 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. Headquartered in San Francisco and Dublin, the company aims to increase the GDP of the internet.
| Field | Value |
|---|---|
| Industry | Technology, Information and Internet |
| Company size | 5,001-10,000 employees |
| Headquarters | South San Francisco, California |
| Organization type | Privately Held |
| Year founded | 2010 |
| Open jobs on Jobsy | 49 |
| View page |
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)
Journal
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