Role Overview

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

Responsibilities

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.

Responsibilities

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 standards

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 models
Qualifications
Honours or Master’s degree in Mathematics, Statistics, Computer Science, Actuarial Science, or a related quantitative field

Preferred Profile

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 growth

Conditions of Employment

Clear criminal and credit record