Press Tab to Move to Skip to Content Link
ResponsibilitiesThrough analysis, aim to identify anomalies, and provide actionable recommendations that mitigate risk, reduce financial losses, and protect both customers and stakeholders from the impact of fraudulent behaviour.Extracting, analysing, and linking of data from multiple sources and systems to detect fraud trends that will influence strategy and the writing of expert fraud rules.Implementing and operationalising fraud mitigation and analysing the effectiveness thereof through dashboards and metrics.ExperienceMinimum: At least 3 years' experience within an analytical environment, including application of SQL, Power BI and advanced Excel functions.Ideal: 3+ years' experience within a fraud/risk analytical environment, including application of SQL, Power BI and advanced Excel functions.Fraud analysis experience.Qualifications (Minimum)A relevant tertiary qualification in Information Technology - Computer Science or Statistics.Qualifications (Ideal or Preferred)Bachelor's Degree in Information Technology - Computer Science or Information Technology.KnowledgeMinimum: Proficiency in data analysis techniques and statistical methods to identify anomalies and patterns indicative of fraud. Knowledge of fraud detection methods, such as rule-based systems, anomaly detection, and predictive modelling.Strong knowledge of SQL for querying databases and extracting relevant data for analysis. A basic understanding of machine learning concepts and algorithms, including supervised and unsupervised learning.Familiarity with data visualization tools and techniques for creating informative dashboards and reports.Ability to identify and address complex fraud-related challenges and develop effective solutions.In-depth knowledge of query and scripting languages to extract, manipulate, and analyse large datasets, uncovering hidden patterns and anomalies indicative of fraudulent behaviour.Develop advanced predictive models that can adapt to evolving fraud tactics.Ideal: Understanding and knowledge of:Internal MIS data base tables/table structures.AWS.Proficiency in a scripting language (e.g., Python) for data manipulation, scripting, and model development.SkillsAnalytical SkillsNumerical Reasoning skillsPlanning, organising and coordination skills
#J-18808-Ljbffr
