Data Analyst - Fraud Monitoring

At a glance

Are you passionate about both advanced analytics and fraud detection? Do you have the expertise to instil the statistical thinking in team’s way of working? If so, we have the perfect role for you!

Channel Security is seeking a Data Analyst to join our team;
Fraud Monitoring. In this role, you will be a technical expert and a strong individual contributor who will bring the analytics maturity in a team with a business-driven background. You will serve as an important pillar for improving analytics standards and help shape the way we use data to make impactful decisions in protecting our customers.

As a Data Analyst within the Fraud Monitoring team, you will play a central role in ensuring that our analysis and detection logic are grounded in solid reasoning and supported by evidence. You will work closely with Fraud Experts (FEs), Data Analysts, and Data Scientists to strengthen our fraud detection capabilities to catch frauds such as phishing, account takeover, scams, and other emerging threats.

Your work focuses on deep‑dive analysis, understanding fraud behaviour, evaluating the effectiveness of detection logic, and validating whether proposed changes are analytically sound. You will help the team distinguish clear signals from noise, recognise when evidence is insufficient, and ensure our decisions are based on robust data rather than anecdotal cases.

This is a hands‑on analytical role with significant influence: your insights and your methodological judgment will directly shape how we detect fraud and protect our customers.

Grid Channel Security is responsible for the prevention and detection of payment fraud and deciding the policy and strategy in the area of fraud. The Fraud Monitoring team that you are going to be part of, is a motivated multidisciplinary group working with a focus on protecting customers. We work in a hybrid way and our day-to-day work is organized by the agile and scrum principles.

You are a proactive self-starter with a keen eye for data analysis questions. You don’t need to be told what to do. Instead, you’ll look for insights people haven’t thought of yet before or didn’t have the time or skills (yet) to succeed. You are able to present the insights and have a strong capability of mentoring your colleagues in doing the same.

Key Responsibilities:

• Analytical Excellence
• Perform in‑depth analyses to understand fraud patterns, attack vectors, seasonality, behavioural shifts, and detection performance across payment channels.
• Evaluate the strength of proposed detection logic (features, thresholds, rules) and identify when ideas are overly narrow, unsupported by evidence, or prone to false positives.
• Assess the value and reliability of data fields and signals used in fraud detection.
• Help ensure our reasoning, conclusions, and decisions are analytically sound and well‑supported.

Methodological Leadership:

• Coach colleagues on interpreting data responsibly, avoiding common analytical pitfalls, and understanding basic statistical concepts such as variance, sample bias, and signal strength.
• Promote a culture of analytical rigor — ensuring the team adopts more mature, data‑driven ways of working.

Collaboration & Impact:

• Partner with Data Scientists to transform analytical insights into hypotheses, experiments, and feature ideas for model development.
• Act as a bridge between domain experts and technical experts, ensuring clear understanding on both sides.
• Be decisive in bringing data driven insights to production system to maximize the impact in safeguarding customers.
• Identify opportunities to improve how we measure fraud impact, effectiveness of controls, and operational efficiency.

Qualifications and technical skills:

• A master’s…