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Full-time
bachelor degree, postgraduate degree
Posted 9d ago
~40 hrs/week
Responsibilities
You will build and improve machine learning models to power fraud detection and loss management systems. You will also collaborate with engineering and operations teams to move research into production and derive actionable insights.
Requirements
Candidates must have a degree in a quantitative field with 1-8 years of experience depending on the level of education. Proficiency in SQL, Python or R, and experience in fraud or risk modeling are required.
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.
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)
Related keywords
Data ScienceFraudRiskFinancial CrimeMachine LearningSQLPythonRStatistical ModelingCausal InferenceOptimizationExperimentationSparkHadoopData ProductsAnomaly Detection
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.
Offices: 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