Job Overview
Analyst — AI Fraud Detection & Payment Intelligence
Location: Kuwait — Fully Remote with regional collaboration
Seniority Level: Senior Analyst / Advanced Analytics
Employment Type: Full-time, Permanent
Industry Focus: Fintech, AI, Fraud Analytics, Payments, Machine Learning, Risk Intelligence
ENTER THE INTELLIGENCE LAYER
Modern financial fraud does not always announce itself.
It appears as a subtle behavioural deviation, an unusual transaction sequence, an unexpected device pattern or a network of apparently unrelated accounts.
The Analyst will investigate these signals using advanced analytics, machine learning and financial intelligence to identify suspicious activity and strengthen digital-payment environments.
This is a role for an analytical professional who enjoys solving problems where technology, mathematics and human behaviour intersect.
THE ANALYTICAL MANDATE
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Analyse transaction data for anomalous activity.
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Develop fraud-detection indicators and behavioural-risk signals.
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Support machine-learning models designed to identify suspicious patterns.
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Analyse transaction velocity, frequency, value and behavioural deviations.
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Investigate complex fraud cases and emerging typologies.
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Develop analytical dashboards for operational and executive teams.
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Monitor model performance and detection effectiveness.
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Analyse false positives and recommend optimisation strategies.
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Identify relationships between customers, accounts, devices and transaction networks.
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Collaborate with engineering and data-science teams to improve detection infrastructure.
INTELLIGENCE METHODOLOGY
Behavioural Analytics
Determine whether current activity differs materially from established customer behaviour.
Transaction Intelligence
Identify unusual transaction volumes, frequencies, values and sequences.
Network Analytics
Investigate relationships among accounts, devices, merchants and transaction flows.
Predictive Analytics
Use statistical and machine-learning methodologies to estimate potential financial risk.
Decision Intelligence
Translate analytical findings into practical actions for fraud and operations teams.
TECHNICAL CAPABILITY
Preferred experience includes:
SQL • Python • Machine Learning • Statistical Analysis • Data Visualisation • Predictive Modelling • Anomaly Detection • Network Analysis • Financial Analytics
PERFORMANCE INDICATORS
Your contribution will be measured through:
Detection Precision → Loss Prevention → False-Positive Reduction → Investigation Efficiency → Model Performance → Response Time
IDEAL PROFILE
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4–8 years in fraud analytics, fintech, banking analytics, risk intelligence or data science.
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Strong quantitative and analytical background.
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Excellent SQL and statistical-analysis capabilities.
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Python or equivalent programming experience advantageous.
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Understanding of payment systems and transaction behaviour.
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Experience working with machine-learning models.
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Strong investigative reasoning and attention to detail.
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Ability to explain complex analytical findings clearly.
INDICATIVE PACKAGE
KWD 2,500–4,000 monthly, depending on experience and analytical specialisation, with potential performance incentives and additional benefits.
THE ANALYTICAL EDGE
Fraud detection is not simply about finding suspicious transactions.
It is about recognising the pattern before the pattern becomes the loss.
Don’t miss the chance to make a difference in the fintech and FX industry!
Apply now by clicking on the “Apply Now” button below.
Let’s shape the future of finance together!
#EmploySolutionJobs #FXCareers.
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