Quantitative Analyst at Network Recruitment

Key Responsibilities:

• Build and develop credit scorecards from the ground up using Python and advanced statistical methods.
• Design, implement, and maintain credit risk models to assess and predict customer behavior.
• Utilize data science techniques to transform large datasets into actionable insights.
• Work closely with cross-functional teams to ensure models align with business goals and industry best practices.
• Conduct rigorous testing and validation to ensure model accuracy and scalability.
• Present model results to senior stakeholders and provide key insights to drive business decisions.

What We’re Looking For:

• Mid-level or Senior candidates with experience in building credit scorecards from scratch.
• Proficiency in Python, with expertise in data analysis, machine learning, and statistical modelling.
• In-depth knowledge of credit risk domains such as personal loans, credit cards, and vehicle finance.
• Strong experience with SQL and managing large datasets.
• Mid-level candidates: 2-4 years of experience in scorecard modelling.
• Senior candidates: 5+ years of experience in building and maintaining complex scorecards.
• A BSc Honours (or equivalent) in Mathematics, Statistics, Actuarial Science, or related field.