Analyst III (IT) (319003)

Channel Security is seeking a Lead Data Analyst to join our Fraud Monitoring team. In this role, you will not only be a technical expert and a strong individual contributor but also a key leader in advancing the analytics maturity of a team with a business-driven background. You will serve as a pillar for analytics standards and help shape the way we use data to make impactful decisions.

At a glance

Are you passionate about both advanced analytics and empowering others to grow in their analytical capabilities? Do you have the expertise to lead by example while fostering a culture of statistical thinking? If so, we have the perfect role for you!

Your job

As a Lead 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 Scientists, and Machine Learning Engineers to strengthen our fraud detection capabilities across payment channels to catch frauds such as phishing, account takeover, lost or stolen cards, 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.

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

• Guide Fraud Experts and junior analysts in applying good analytical practices and critical thinking.
• 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.
• Identify opportunities to improve how we measure fraud impact, effectiveness of controls, and operational efficiency.
• Drive improvements in how we use data in the team — from investigation workflows to decision support tools — focusing on quality, clarity, and insight rather than dashboard volume.

Working environment

Grid Channel Security within Corporate Information Security Office (CISO) 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 of approximately 25 colleagues 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. CISO is recognised as having an informal work atmosphere where everyone has a heart for their job and is prepared to help others.

Your profile

Qualifications and technical skills:

• A master’s degree in a quantitative field (e.g., Computer Science, Statistics, Econometrics, Engineering, Physics, Mathematics, or similar).
• At least 3 years of experience in an analytical role involving hands-on data exploration, problem solving, and interpretation (e.g., data analyst, fraud analyst, risk analyst, business analyst with strong technical skills, data scientists in analytical track).
• Strong SQL skills for exploratory analysis and investigation.
• Hands-on experience in Python for data analysis.
• PySpark or experience working with large datasets.
• Basic familiarity with visualization tools for communication — not for dashboard engineering.
• Ability to frame analytical questions, interpret results correctly, and identify flawed logic or insufficient evidence.
• Familiarity with basic statistical concepts (e.g., distributions, variance, seasonality, sampling, simple backtesting principles). Not as a statistician— but as a critical thinker.
• Excellent written and verbal communication skills in English.
• Ability to work independently and as part of a team.

About you

• You are an energetic Firestarter, proactively looking for and finding relevant data analysis questions.
• Strong critical thinking and the confidence to challenge weak assumptions.
• Ability to clearly articulate reasoning, uncertainties, and trade-offs.
• A Teacher and Mentor with a deep passion for upskilling and helping your fellow team members grow their analytical capabilities, especially guiding them to adopt statistical rigor during their analytical work.
• Experience and understanding of Scrum and Agile methodologies, with the ability to apply these frameworks effectively in project management and team collaboration.

We are offering

• Flexibility in a hybrid work environment to support strong work-life balance;
• An industry-competitive salary based on a 36 or 40-hour work week;
• A supplementary benefit budget of 11%, which you can spend on pre-tax fringe benefits;
• A personal development budget of EUR 1.000 per year;
• An annual public transportation pass;
• A solid pension plan.