Senior Analyst / Analytics Manager – Fraud Risk X 2

emagine is looking for 2 experienced Fraud Risk Analyst / Analytics Managers to join a high-performing Fraud team.

The consultants will play a key role in designing, testing, and deploying real-time fraud prevention and detection strategies, combining business rules and machine learning models across multiple products and markets.

Start: within 1 month

Duration: TBD

Location: Stockholm, 3 days/week onsite

About the assignment

• Develop and optimize real-time fraud decisioning strategies, integrating both rule-based logic and ML-driven models.

• Analyze large-scale event data to detect and prevent emerging fraud patterns such as account takeover, synthetic identities, mule activity, refund abuse, and first- or third-party fraud.

• Conduct A/B testing and champion/challenger experiments, continuously monitoring KPIs such as precision/recall, false positive rate, approval rate, loss basis points, chargeback rate, and customer friction.

• Partner closely with Engineering, Product, and Data Science teams to build detection features, enhance signal pipelines, and operationalize fraud countermeasures.

• Lead incident response during fraud spikes, providing rapid mitigation, structured post-mortem analyses, and lessons learned.

• Assess and integrate third-party vendor signals (device fingerprinting, identity, behavioral, telco, sanctions/PEP, 3DS) where they provide measurable improvement.

• Translate insights into clear, actionable rollout plans, supported by monitoring dashboards, alerting frameworks, and stakeholder communication.

Competence and Experience

Must-haves:

• 3–8+ years of experience in fraud analytics, credit risk, or decisioning within payments and consumer finance

• Strong analytical and technical skills with hands-on experience in SQL and Python or R.

• Proven ownership of a fraud or credit policy/modeling strategy with measurable impact on KPIs.

• Solid understanding of experiment design (A/B testing, champion/challenger frameworks) and post-deployment performance monitoring.

• Excellent communication skills, able to collaborate with senior stakeholders and drive data-informed decisions quickly.

Nice to have:

• Familiarity with the fraud vendor ecosystem (device fingerprinting, identity graphs, behavioral biometrics, 3DS/SCA).

• Understanding of PSD2, SCA, 3DS, and Transaction Risk Analysis (TRA) and how to design compliant yet conversion-friendly controls.

• Experience using LLM-assisted tools for case investigation, summarization, or automation of manual review processes.

• Prior experience being on-call during fraud incidents, with proven ability to perform under pressure.