Fraud Data Scientist at Luno

Identifying opportunities in the business that could benefit most from cognitive applications, as well as building and enhancing organisational capabilities for deriving value from multiple data sources using data science.

Your Mission Will Involve

• Building, deploying and maintaining fraud detection models using advanced statistical and machine learning techniques to ensure our fraud prevention strategy is up to date
• Working with cross-functional teams of engineers, product, and operations to design and monitor fraud risk strategies to help mitigate fraud and other security risks as accurately as possible
• Using behavioural analytics to proactively surface patterns, trends, and anomalous behaviours that help minimise the company's exposure to financial and reputational risk
• Building dashboards to facilitate operational and exploratory analysis of fraud
• Developing, implementing and maintaining effective risk management programmes to align with the business needs
• Identifying problems, defining solutions, executing plans, measuring and communicating results on a regular basis

The Ideal Candidate Will Have The Following Essentials

• Bachelor's degree or higher in the natural sciences or technical field such as Mathematics, Statistics, Computer Science, or Engineering
• A minimum of 2 years experience in a similar role
• A strong bias for applied research in exploratory data analysis, anomaly detection, predictive modeling, classification and optimisation
• Strong interpersonal and communication skills
• The ability to communicate insights to non-technical audiences
• The ability to work independently, as well as within and across teams
• The drive to successfully complete projects with large and/or incomplete data sets
• Adaptability, resilience, and are able to thrive in a fast-paced environment
• A growth mindset, and eager to learn and expand your skill set
• Enthusiasm to work in the cryptocurrency space

What Will Set You Apart

• A postgraduate qualification in a relevant discipline
• Professional certification in a data science-related field from a reputable entity
• A strong foundation in data structures, algorithms, statistics, and machine learning
• Experience working in fraud detection and prevention
• Subject matter expertise and experience in using information generated from fraud patterns, data analytics and business knowledge to generate insights and formulate an action plan