Data Scientist II — Financial Crime Analytics

firstrand; Johannesburg; On-site; ZAR 540,000 - 900,000; Full time

Benefits offered by this job

Networking opportunities

Challenging work

Innovative projects

Job summary

FirstRand invites applications for a data scientist role focused on quantitative analytics to plan, build, optimise and implement advanced models for financial crime analytics. You will translate complex methods into actionable insights for business stakeholders.

You will join a diverse talent team and work across risk, technology and business units to improve model effectiveness and compliance while supporting junior data scientists.

Qualifications

• Honours degree in Mathematics, Statistics, CS, Actuarial Science, Engineering, Physics, or related field.

Responsibilities

• Deliver on model development, implementation and governance for financial crime analytics.
• 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 to drive model effectiveness and compliance.
• Support junior Data Scientists in developing technical and business skills.
• Apply SAS, SQL and Python for data manipulation, modelling and automation.
• Uphold model governance standards and participate in monitoring.
• Demonstrate initiative and a solution-oriented mindset in high-stakes, regulated environments.

Skills

SAS

SQL

Python

Education

Honours degree in Mathematics, Statistics, CS, Actuarial Science, Engineering, Physics, or related field

Tools

SAS

SQL

Python

Job description

FirstRand invites applications for a data scientist role focused on quantitative analytics to plan, build, optimise and implement advanced models for financial crime analytics. You will translate complex methods into actionable insights for business stakeholders.

You will join a diverse talent team and work across risk, technology and business units to improve model effectiveness and compliance while supporting junior data scientists.