Validation Analyst (Decision Science)

SUMMARY:
Are you passionate about data, risk, and building challenger models that keep decision-making sharp? Join a fast-growing bank’s Model Validation team and play a critical role in shaping the future of credit risk, finance, and fraud prevention.

POSITION INFO:
This innovative and client-focused financial services group is redefining banking to make it simple, accessible, and personal. They’re on a mission to build the best bank in the world — and they need energetic, self-motivated professionals who want to make a real impact.

As a Model Validation Analyst, you’ll work in a high-performing Decision Science team, taking end-to-end ownership of model validations, building challenger models, and ensuring compliance with risk management and regulatory standards.

Why You Should Join:

• Be part of a company that invests in people, culture, and innovation
• Work on a diverse range of models across credit, finance, fraud, and capital
• Collaborate with some of the brightest minds in data science and risk
• Access to growth opportunities, training, and a supportive team culture

• Perform independent validations of credit risk, finance, and fraud detection models
• Build and implement challenger models to ensure robustness and accuracy
• Partner with Model Developers and business teams to provide technical challenge and assurance
• Monitor model performance, identify risks, and contribute to framework improvements

• Education:
  • Minimum: Degree in Mathematics, Statistics, Actuarial Science, or Data Science
  • Preferred: Honours Degree in Data Science, Statistics, Mathematics, or Actuarial Science
• Experience:
  • 3–6 years of scorecard building and validation experience (credit risk, behavioural, or marketing models)
  • Proven experience with data mining and predictive modelling
  • Deep understanding of the credit lifecycle
  • Previous exposure to regulatory requirements and model governance an advantage
• Skills:
  • Strong analytical and problem-solving skills
  • Proficiency in SQL, Python, or R
  • Excellent stakeholder engagement and communication abilities
  • High attention to detail and the ability to work independently

• Actuarial roles (Life, Short-Term, Health, Pensions, and Quantitative)
• Data Scientists / Data Analysts (Python, R, SQL, and Machine Learning)
• Risk Analysts (Credit, Market, Model Risk, and Operational)
• Pricing Specialists (Insurance and Financial Products)
• Machine Learning & AI Data Scientists (ML Ops, NLP, and Predictive Modelling)
• Quantitative Specialists across Banking, Insurance, and FinTech