Analyse risk, transaction, operational, and business data to identify trends, patterns, anomalies, and potential areas of concern.
Write and optimise SQL queries to extract, transform, validate, and analyse data from multiple sources.
Use Python for data analysis, data preparation, automation, reporting, and development of analytical solutions.
Design, build, and maintain interactive dashboards and reporting systems to monitor key risk and operational metrics.
Translate business and stakeholder requirements into meaningful reports, dashboards, analytical models, and actionable insights.
Automate recurring reports, data preparation activities, monitoring processes, and other manual workflows to improve efficiency and accuracy.
Perform root-cause analysis on operational issues, risk incidents, data discrepancies, and performance trends.
Establish data validation and quality checks to ensure the accuracy, completeness, and consistency of reports and dashboards.
Identify opportunities to improve existing processes through data analysis, automation, and better use of technology.
Collaborate with Risk, Operations, Product, Technology, and Business teams to understand requirements and deliver effective analytical solutions.
Present analytical findings and recommendations clearly to technical and non-technical stakeholders.
Explore and apply relevant AI tools to support data analysis, insight generation, dashboard development, documentation, and process automation, while ensuring appropriate review of outputs.
Maintain documentation for queries, dashboards, reporting logic, processes, and analytical methodologies.
Stay informed about developments in risk analytics, data visualisation, automation, and AI applications relevant to the fintech and payments industry.
Requirements:
Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or another quantitative discipline.
Relevant experience in data analytics, business intelligence, risk analytics, operations analytics, or a related field.
Hands-on experience in building, maintaining, and improving dashboards using tools such as Tableau, Power BI, Looker, or similar platforms.
Experience in automating reports, dashboards, data workflows, or recurring operational processes.
Familiarity with AI tools and their applications in analytics, reporting, data exploration, documentation, or workflow automation.
Strong analytical and problem-solving skills, with the ability to work with large and complex datasets.
Ability to identify trends, investigate discrepancies, perform root-cause analysis, and derive actionable insights.
Ability to collaborate effectively with cross-functional stakeholders and manage multiple priorities.
Proactive, detail-oriented, and comfortable working independently in a fast-paced environment.
Experience in fintech, payments, banking, financial services, fraud, or risk operations would be an advantage.
