Data Analyst, Revenue Protection (Investigations)

Role Overview

The Data Analyst, Revenue Protection (Investigations) will work with large sets of client betting data to identify gaps, discrepancies or unusual patterns and investigate their cause. The role involves building a clear case for Sales and Legal to take forward with the client, then following each case through to resolution and measuring the outcome.

What You Will Do

The Data Analyst will analyse client betting data to spot anomalies and changes in behaviour, build the evidence behind each finding, estimate the revenue impact of an infringement, and write short, precise findings for non-technical stakeholders.

Why It Might Be a Fit

The ideal candidate will have 2+ years of experience in a data-led investigative role, strong Excel skills, and the ability to uncover wrongdoing, non-compliance or revenue leakage through data analysis.

Requirements

• 2+ years of experience in a data-led investigative role
• Experience in betting or sports data is preferred, but we also welcome strong backgrounds in fraud, risk, financial crime, payments, revenue assurance, trading risk, integrity or similar areas
• Strong Excel skills, including pivot tables, lookups, cleaning and reconciling large datasets, and building calculations that others can review and validate
• Working knowledge of SQL, with the ability to pull, filter and aggregate data from large tables independently
• Clear and concise writing skills, with the ability to explain complex findings to people who may not know the underlying data
• Curiosity and persistence, with the drive to keep digging until the explanation holds

Benefits

• A collaborative environment with colleagues from all over the world
• Flexibility to manage your workday and tasks with autonomy
• A balance of structure and autonomy to tackle your daily tasks
• Vibrant and inclusive community, including Women in Tech and Pride groups
• Global Employee Assistance Programme
• Calm and Reulay app
• Online training videos
• Flexible working hours

Tagged as: Data Analysis