SAS AML Data Scientist

Our client is seeking an experienced SAS AML Data Scientist to develop and optimise data-driven solutions that strengthen anti-money laundering detection and financial crime prevention. This contract position is office-based and requires strong SAS development, advanced SQL, and analytical expertise, together with an understanding of AML processes and regulatory requirements.

Key Responsibilities

• Develop, implement, validate, and optimise predictive models and machine learning algorithms for AML detection.
• Configure and integrate analytical models into SAS AML scenario management, scoring, and case management processes.
• Extract, clean, transform, and analyse large datasets using Base SAS, SAS Macro, SAS/SQL, and related technologies.
• Perform model validation, back-end testing, monitoring, and scenario tuning to improve detection accuracy and reduce false positives.
• Develop reports and visualisations to communicate findings to Compliance, Risk, and senior stakeholders.
• Maintain high standards of code quality, version control, testing, and deployment within an Agile environment.
• Collaborate with technical and business stakeholders to translate business requirements into software specifications and effective technical solutions.

Minimum Requirements

• A Bachelor's or Master's degree in Computer Science, Information Technology, Finance, or a related quantitative discipline.
• At least four years of hands-on SAS development experience, preferably within AML, financial crime, or regulatory compliance.
• Practical experience with SAS AML, including scenario management, case management workflows, and AML data models.
• Expert-level SQL skills, including complex queries, joins, subqueries, views, stored procedures, functions, and query optimisation.
• Experience with relational databases such as Oracle, SQL Server, DB2, PostgreSQL, or similar platforms.
• Strong understanding of AML, KYC, Customer Due Diligence, and relevant financial crime regulations.
• Experience working in Agile or DevOps environments.
• Strong analytical, problem-solving, communication, and documentation skills.

Advantageous Skills

• Experience with SAS Viya 4, SAS Visual Data Mining and Machine Learning, SAS/STAT, and SAS Data Integration Studio.
• Knowledge of Python or R for machine learning and analytical development.
• Familiarity with Unix/Linux, shell scripting, Git, CI/CD tools, and data visualisation platforms.
• Exposure to cloud-based data platforms and model governance frameworks.

Work Environment

• Office-based contract position.
• Overtime may be required to meet project deadlines.
• Occasional travel may be necessary.

If you would like to apply for this position, please send transcripts with applications.

Should you meet the requirements for this position, please email your updated CV attached to ***email_hidden***, alternatively contact 031 350 4018 or visit our website, www.tumaini.co Correspondence will only be conducted with short listed candidates. Should you not hear from us within 3 days, please consider your application unsuccessful.