Trading Data Analyst

Let's start with the role

We are looking for a Trading Data Analyst to join our fast-growing BI & Analytics team and help drive the expansion of our Kaizen Gaming functions in an exciting scale-up data journey. Your main focus will revolve around Trading-related subjects, such as market performance, league standings, sport results and betting activities, along with customer and operation-focused analyses, among others.

• Build close relationships with the Trading Teams;
• Proactively provide data analytics and insights autonomously as a Subject Matter Expert (SME);
• Analyze KPIs with a clear view of results vs. expected targets;
• Effectively communicate insights and recommendations to stakeholders to help them make better-informed business decisions;
• Receive priorities directly from the function;
• Have a solid understanding of the tools utilized by the Trading function, along with the data they generate and how it can be leveraged to extract insights;
• Continuously question existing metrics and KPIs, collaborating closely with the Business Intelligence (BI) team to develop the new metrics and KPIs designed to propel business growth;
• Oversee data Integration: Coordinate the integration of data from diverse internal and external sources, such as game providers, payment gateways, and other systems, ensuring data consistency and reliability across systems;
• Collaborate closely with the BI team to ensure alignment, adoption of best data visualization practices and seamless information exchange between central and peripheral teams;
• Drive towards establishing a strong data culture across the organization;
• Design and develop data intelligence including the analysis, reporting and dashboards of key metrics and KPIs.

What you’ll bring

• Bachelor’s/Master’s degree in a quantitative discipline such as statistics, mathematics, economics, operations research, or similar;
• At least 3 years of working experience in a reporting, statistical or quantitative role;
• Work experience in the gaming industry would be considered a plus;
• Exceptional data storytelling skills and the ability to articulate technical information to a non-technical audience;
• Ability to think strategically and primarily cooperate and interact with senior stakeholders;
• Advanced SQL skills, highly advanced with MS Excel and Google-sheets (pivot tables, v-lookups);
• Working experience with Microsoft Power BI would be considered a plus (or other dashboarding tools such as Tableau);
• Working experience with Python would also be considered a plus (especially Pandas, Numpy, and other relevant libraries for data analysis).