
Senior Analyst/Analytics Manager-Fraud Risk
at Klarna
Posted 12 hours ago
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- Compensation
- Not specified
- City
- Not specified
- Country
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Currency: Not specified
This role involves designing and deploying real-time fraud decisioning strategies using rules and machine learning models, analyzing large volumes of data to detect fraud patterns, and collaborating closely with multiple teams. The position requires hands-on experience with SQL and Python or R, strong experiment design skills, and ownership of fraud or credit policies with measurable impact.
What you will do
In this role, you will design, test, and deploy real-time fraud decisioning strategies - combining rules and ML models across products and markets, while analyzing high-volume event data to uncover emerging patterns such as account takeover, synthetic identities, mule activity, refund abuse, and first- or third-party fraud. You’ll run champion/challenger experiments and A/B tests and continuously monitor precision/recall, false-positive rate, approval rate, loss bps, chargeback rate, and customer friction. You’ll build detection features and signal pipelines in close partnership with Engineering, Product, and Data Science; lead incident response during fraud spikes with clear mitigations and post-mortems; and evaluate and integrate vendor signals device, identity, behavioral, telco, sanctions/PEP, and 3DS where they deliver measurable lift. Above all, you’ll translate insight into action through clear, concise specifications and rollout plans, supported by alerting dashboards and stakeholder updates that drive fast, high-quality decisions.
Who you are
3–8+ years in fraud strategy/analytics or credit underwriting/risk decisioning within payments, consumer finance, or large-scale e-commerce
Hands-on with SQL and Python or R to prototype analyses and experiments
Ownership of a production fraud/credit policy or modeling strategy with demonstrated KPI impact
Strong experiment design skills (A/B testing, champion/challenger), metric trade-off evaluation, and post-deployment monitoring
Excellent communication with senior stakeholders; able to influence and drive decisions quickly
Awesome to have
Experience with fraud/risk vendor ecosystem (e.g., device fingerprinting, identity graphs, behavioral biometrics, 3DS/SCA) and structured evaluation methods
Knowledge of PSD2/SCA/3DS and TRA exemptions; able to design compliant controls without harming conversion
Exposure to LLM-assisted investigations (case summarization, entity extraction, workflow automation)
On-call support experience during active fraud attacks and ability to perform under pressure
Please include a CV in English.
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