Quantitative Analyst

You will be independently validate highâimpact models across credit risk, financial crime, and advanced analytics use cases. This is a handsâon 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, Cat Boost, Neural Networks)
• Unsupervised learning (clustering, isolation forests)

Managing model risk across the endâtoâend model lifecycle, including:

• Feature engineering and data preparation
• Model training, evaluation, and selection
• Production deployment and monitoring
• Building and reviewing models in Pythonâbased environments

Partnering closely with Risk, Technology, and Business stakeholders. Ensuring models meet governance, performance, and scalability standard.

What We Are Looking For

58 years relevant experience Strong handsâon experience building machine learning and data science models endâtoâend Proven use of techniques such as:

• Boosting algorithms (XGBoost, Cat Boost)
• Neural networks
• Clustering and anomaly detection

Advanced proficiency in Python Solid experience with SQL and working with large, complex datasets

Experience with in 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 Masters 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 IFRSârelated 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 highâimpact, 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. Should you not receive a response from us within one week of your application, your application has unfortunately not been successful.