Quantitative Analyst

Reference: JHB000944-SNDV-2

Our client is looking for a Quantitative Analyst to join their collaborative and fast-growing team. Duties & Responsibilities

Quantitative Analyst - Machine Learning Data Science You will be independently validate high‑impact models across credit risk, financial crime, and advanced analytics use cases. This is a hands‑on technical role.

What You'll Be Doing

• Independent validation of machine learning models across:

• Credit risk models

• Propensity and behavioural models

• Financial crime models (fraud and AML)

• Applying advanced ML techniques, including:

• Supervised learning (Random Forest, XGBoost, CatBoost, Neural Networks)

• Unsupervised learning (clustering, isolation forests)

• Managing model risk across the end‑to‑end model lifecycle, including:

• Feature engineering and data preparation

• Model training, evaluation, and selection

• Production deployment and monitoring

• Building and reviewing models in Python‑based environments

• Partnering closely with Risk, Technology, and Business stakeholders

• Ensuring models meet governance, performance, and scalability standard

What We Are Looking For

• 5–8 years relevant experience

• Strong hands‑on experience building machine learning and data science models end‑to‑end

• Proven use of techniques such as:

• Boosting algorithms (XGBoost, CatBoost)

• Neural networks

• Clustering and anomaly detection

• Advanced proficiency in Python

• Solid experience with SQL and working with large, complex datasets

• Experience within credit risk, propensity modelling, or financial crime analytics

• Experience with independent validation of models and/or detailed peer review

• Proven experience researching machine learning model

Qualifications

• Honours or Master’s degree in Mathematics, Statistics, Computer Science, Actuarial Science, or a related quantitative fiel

Preferred/ Ideal

• Experience deploying or supporting models in cloud environments

• Exposure to credit risk modelling, scorecards, or IFRS‑related analytics

• Financial crime (fraud or AML) modelling experience

• Experience designing models with scalability and deployment in mind

• Familiarity with model risk, governance, or validation standard

What's in it for you?

• Work on high‑impact, real-world models used across the industry.

• Exposure to a wide variety of models, not just one product or portfolio

• Learn from experienced quantitative leaders in a collaborative environment

• Be part of a fast-growing organisation that values simplicity, transparency, and ownership

• Competitive rewards, learning opportunities, and long-term career growt

Conditions of Employment

• Clear criminal and credit record

Should you not receive a response from us within one week of your application, your application has unfortunately not been successful.

You can visit our website for more vacancies: www.wePlace.co.za / www.linkedin.com/company/wePlace