Data Analyst Cards

At a glance

Are you passionate about fraud detection and data analytics? Do you have the skills to cut through the noise and uncover the real signal in the data? Do you bring a statistical mindset to your analysis and turn insights into action? If so, we have the perfect role for you!

Channel Security is seeking a Data Analyst to join our Fraud Monitoring team. In this role, you will be a technical expert and a strong contributor helping advance the analytics maturity of the team. You will play a pivotal role in leveraging the data to make impactful decisions about fraud prevention and detection.

As a Data Analyst, in the Grid Channel Security, you will work together with fraud experts, data scientists and machine learning engineers to safeguard our customers from criminals. This includes threats such as phishing, account takeover, lost or stolen debit cards, e-commerce fraud, and more.

You will be a vital bridge between our fraud experts and data science team, with your insights acting as catalysts for advancing our fraud detection strategies. In this role, you’ll also be responsible for understanding different types of frauds, connecting your knowledge to what’s happening on the ground and proposing solutions to tackle emerging threats. Alongside focused analysis, you will be collaborating with your colleagues to brainstorm how innovative data science solutions can help us stay one step ahead of criminals in the ongoing cat-and-mouse game.

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 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.

You are a proactive self-starter with a keen eye for data analysis questions. 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 these insights clearly to your colleagues and stakeholders.

Key Responsibilities:

• Analyse complex datasets to extract actionable insights that strengthen fraud detection strategies;
• Identify fraud trends across multiple payment channels;
• Partner with data scientists to transform insights into hypotheses and experiments to improve fraud detection;
• Fostering the collaboration between data scientists and business experts;
• Proactively look for and drive improvements in our analytics, including reporting, dashboarding and data-driven decision making.

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 2 years’ experience as a Data Analyst or in a similar role;
• Proficiency in data analysis tools and software, experience and exposure to at least 3 from the list below:
• SQL (must have)
• Python (must have)
• Databricks / Snowflake, or other Cloud analytics environments
• MS Power BI, Tableau, Google Looker
• Pyspark and Apache Hive
• No-SQL technologies (Mongo DB, Elastic Search or similar)
• Knowledge of financial fraud (nice to have)
• 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;
• A Technical Expert with strong analytical skills and experience in applying statistical techniques to real-world business problems;
• A Problem Solver who thrives on tackling complex challenges and delivering actionable insights;
• Experience and understanding of Scrum and Agile methodologies, with the ability to apply these frameworks effectively in project management and team collaboration;
• Ability to maintain accuracy and thoroughness in work, ensuring that documentation, data analysis, and project…