Manager - Fraud Intelligence and Analytics.Risk

Roodepoort, Gauteng, South Africa (Hybrid)

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Fraud Pattern Discovery & Modelling

• Analyse financial transaction flows (P2P, merchant payments, cash-in/out, wallet funding, withdrawals) to identify fraud patterns, typologies of unauthorized transfers, mule account networks, and high-velocity transactional attacks and any other relevant abnormal behaviours.
• Translate observed fraud schemes into data-driven patterns, features, and model hypotheses.
• Design and build machine-learning models to detect and predict:
  • Impersonation and account takeover fraud (SIM swap, social engineering, identity misuse)
  • Transaction laundering and agent gaming (commission abuse, float cycling, abnormal cash flows, collusive transactions)
  • Cyber-enabled fraud (bots, scripted attacks, app tampering)
  • Insider and collusive fraud patterns across users, agents, and merchants
• Perform deep-dive analysis on historical fraud cases to identify emerging patterns and modus operandi
• Continuously refining models based on emerging fraud trends and evolving attacker behaviour.

Advanced Analytics & Machine Learning

• Develop supervised and unsupervised models for fraud detection, including:
  • Anomaly detection (e.g., Isolation Forest, Autoencoders, LOF)
  • Sequence and behaviour-based models for transaction timelines and event chains
  • Pattern-mining approaches to uncover recurring fraud structures
• Apply statistical analysis and explainable AI techniques to interpret model outputs and support operational decisions.

Transaction Data Analysis & Feature Engineering

• Engineer predictive features from multi-source financial and behavioral data:
  • Transactional features: amount, frequency, velocity, time-of-day patterns, beneficiary history, geographic mismatch flags.
  • Device & network intelligence: IMEI/IMSI/ICCID associations, device fingerprinting, VPN/proxy detection, IP reputation, location spoofing signals.
  • Behavioral biometrics: typing dynamics, navigation patterns, session timing, interaction cadence.
• Design scoring frameworks and decision logic for production risk engines, blending model scores with rule-based signals.
• Define and calibrate risk thresholds, alert triggers, and automated actioning (block, step-up auth, review).
• Implement and optimize real-time fraud controls such as geo-fencing, velocity checks, SIM-swap logic, and session risk scoring.

Education

Bachelor's degree in computer science, Data Science, Statistics, Mathematics, or a related field.

MBA and/or master's degree is advantageous

Preferred: Master's degree in data Analytics, Machine Learning, or Cybersecurity

Experience

5 years or more experience in fraud analytics, data science, or risk modeling roles

• At least 3 years' experience within a non-traditional FinTech /ICT/Digital/Fraud Management environment
• Proven track record of building and deploying ML models for fraud detection

Fintech is entering a new phase where operational and commercial excellence has become critical for success. We at MTN believe this is a game changer in terms of our business strategy. We are looking at an incumbent to join us as we build a successful business together.

We at Group Fintech are a purpose and value-led organization.

At Group Fintech, we believe that understanding our people's needs and aspirations is key to creating experiences that delight you at work, everyday. We are committed to fostering an environment where every member of our Y'ello Family is heard, understood and empowered to live an inspired life.

Our values keep us grounded and moving in the right direction. Most importantly, they keep us honest. It is not something we claim to be. It is in our DNA.

As an organisation, we consider it our mission to create an exciting and rewarding place to work, where our people can be themselves, thrive in positivity and ignite their full potential. A workplace that boosts creativity and innovation, improves productivity, and ultimately drives meaningful results. A workplace that is built on relationships and achieving a purpose that is bigger than us. This is what we want you to experience with us!

Our commitments go beyond an organisational promise. It is in our leadership and managerial ethos to meaningfully partner with our employees, customers and stakeholders with a vision to realise our shared goals.

We are delighted that you are considering us as your career partner to make a mark in the world. We look forward to your application!

• Job Identification 7122
• Job Category MTN Level 3
• Posting Date 03/10/2026, 05:33 PM
• Apply Before 03/18/2026, 12:00 AM
• Job Schedule Full time
• Locations MTN Head Office, Innovation Centre, Fairland, Johannesburg (Hybrid)