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 monthDuration: TBDLocation: Stockholm, 3 days/week onsiteAbout The AssignmentDevelop 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 ExperienceMust-haves:3–8+ years of experience in fraud analytics, credit risk, or decisioning within payments and consumer financeStrong 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.