Description

Investec Sandton is looking for a highly data-driven Data Analyst / Data Scientist to support the Financial Crime Compliance team. This role is designed for an individual with strong analytical, statistical, and data modelling capabilities, with a primary focus on enhancing Transaction Monitoring and Suspicious Activity Monitoring (SAM) through data-driven techniques. The role emphasizes advanced analytics, detection optimization, and model development, while still requiring an understanding of business processes, regulatory requirements, and operational workflows within Financial Crime. The candidate will contribute to both project and BAU deliverables, including data analysis, rule tuning, model development, data mapping, validation, and performance monitoring. The role also includes improving alert quality, reducing false positives, and ensuring the effectiveness of transaction monitoring systems.

Key Responsibilities

•    Perform advanced data analysis on transactional and customer data to identify anomalies, patterns, and potential suspicious behaviour.
•    Develop, test, and optimise transaction monitoring rules, thresholds, and detection scenarios.
•    Build and implement statistical and machine learning models for anomaly detection, segmentation, and risk scoring.
•    Translate analytical findings into actionable insights, business rules, and detection strategies.
•    Conduct impact analysis on models, rules, data structures, and monitoring processes.
•    Monitor and evaluate model and rule performance, including false positive rates and detection effectiveness.
•    Document methodologies, model logic, assumptions, and data definitions in line with governance requirements.
•    Participate in the full analytics lifecycle, including data sourcing, preparation, modelling, validation, deployment, and post-implementation monitoring.
•    Support root-cause investigations for data anomalies, model drift, and system-related issues.
•    Work closely with technology and data engineering teams to ensure data quality, availability, and pipeline efficiency.
•    Produce dashboards, visualizations, and reports to support Financial Crime decision-making and regulatory reporting.
•    Communicate insights, risks, and recommendations clearly to technical and non-technical stakeholders.

Qualifications, Experience and Skills

•    7+ years' experience in data analysis or data science, preferably within financial services or financial crime environments.
•    Strong proficiency in SQL and Python, with experience in data manipulation, analysis, and modelling.
•    Experience with machine learning techniques (e.g., classification, clustering, anomaly detection).
•    Strong capability in statistical analysis, pattern recognition, and data-driven problem solving.
•    Experience working with large and complex datasets.
•    Familiarity with AML / Transaction Monitoring / Financial Crime typologies (advantageous).
•    Experience with Microsoft Azure or other cloud platforms is an advantage.
•    Experience working in Agile delivery environments.
•    Understanding of data pipelines, ETL/ELT processes, and data modelling concepts.
•    High ownership, comfort with ambiguity, and ability to work across business and technical teams.
•    Strong communication, storytelling, and documentation skills.
•    Ability to challenge and validate assumptions using data-driven reasoning.

Investec Culture 

At Investec we look for intelligent, energetic people filled with passion, integrity and curiosity. We value individuals who in turn value our culture that is, a flexible attitude comfortable to live with ambiguity and willing to challenge the status quo. Diversity, talent and leadership are respected in pursuit of the growth of our business. People who can manage themselves and build strong relationships in order to get things done, will perform in out of the ordinary ways in our environment. 

We are committed to diversity and inclusion when recruiting internally and externally.