Data Scientist II: AML Analytics & Risk Modeling

FirstRand Limited; Johannesburg; On-site; ZAR 510,000 - 690,000; Full time

Job summary

FirstRand Limited in Johannesburg is seeking a Data Scientist II to design, implement and govern quantitative analytical models for financial crime analytics (AML/CFT, transaction monitoring, sanctions screening).

You will translate complex solutions for non-technical stakeholders, document models, support risk and technology partners, and mentor junior data scientists while applying SAS, SQL and Python.

Qualifications

• 2+ years hands-on experience building analytical models in financial services.
• Proficient in SAS, SQL and Python for data manipulation and modelling.
• Experience in financial crime analytics is a strong advantage.

Responsibilities

• Deliver model development, implementation, and governance for financial crime risk analytics (AML/CFT, transaction monitoring, sanctions screening).
• Proactively identify analytical opportunities and solve unstructured problems with minimal guidance.
• Translate technical solutions into actionable insights for non-technical stakeholders.
• Deliver clear and comprehensive technical documentation for models and processes.
• Collaborate with business, risk, and technology teams across the FirstRand group to drive model effectiveness and compliance.
• Support junior Data Scientists in developing both technical and business skills.
• Apply SAS, SQL, and Python scripting for data manipulation, modelling, and automation.
• Uphold model and rule governance standards and participate in periodic monitoring and reviews.

Skills

SAS

SQL

Python

Analytical thinking

Education

Honours Degree in Mathematics/Statistics/CS/Actuarial Science/Engineering/Physics

Job description

FirstRand Limited in Johannesburg is seeking a Data Scientist II to design, implement and govern quantitative analytical models for financial crime analytics (AML/CFT, transaction monitoring, sanctions screening).

You will translate complex solutions for non-technical stakeholders, document models, support risk and technology partners, and mentor junior data scientists while applying SAS, SQL and Python.