Job Description

To plan, build, optimise and implement innovative quantitative analytical methodologies, procedures, products and advanced
mathematical models that provide analytical support and interpret insights, using advanced analytics technologies, to address business opportunities and problems and implement business strategy.

Job Responsibilities:

• Design, develop, and peer review application scorecards, including reject inference techniques.
• Lead feature engineering initiatives to enhance model performance and business relevance.
• Collaborate with business stakeholders to align scorecard strategies with commercial objectives.
• Apply scoring models across diverse industries, bringing cross-sector insights to credit decisioning.
• Innovate and build predictive solutions in low-data environments, especially for SME lending.
• Provide thought leadership on model governance and industry best practices.
• Mentor and upskill junior analysts and data scientists through structured learning and hands-on guidance.
• Present technical concepts and strategic recommendations to executive-level stakeholders.
• Continuously evaluate and improve scoring methodologies using modern data science techniques.
• Manage multiple projects simultaneously.
• Be a leader in the development of PD models across the broader team, providing insights in best practice for Behavioral model developments.

Required Experience

• Minimum 5 years of hands-on experience in application scoring and credit risk modeling, with multiple completed models.
• Proven expertise in scorecard development, including reject inference and model validation.
• Strong proficiency in feature engineering and data preprocessing techniques.
• Experience working across multiple industries is a bonus (e.g., retail, telecoms, fintech, insurance).
• Ability to work with limited or imperfect data and still deliver robust, actionable models.
• Excellent communication skills with the ability to engage and influence senior business leaders.
• Demonstrated ability to mentor, teach, and learn junior team members, but at the same time drive and motivate the use of scoring to more executive stakeholders.
• Proficiency in tools such as SAS and paragon modeler.
• Experience with model deployment.

Preferred Attributes

• Experience in SME lending or alternative credit scoring.
• Familiar with industry best practice in application scoring.
• Exposure to machine learning techniques in scoring contexts.
• Experience in generating new features to be used in model development.
• Comfortable working in agile, cross-functional teams.

Qualifications

• Bsc/BCom Maths/Statistics/Mathematical Statistics/ BEng
• SAS is a prerequisite
• Paragon modeler experience would be advantageous

Why Join Us?

Work on high-impact projects that shape the future SME lending landscape and credit decisioning across industries.

Be part of a collaborative, innovative, and growth-oriented data science team.

Opportunity to lead and influence the future of scoring in emerging markets and SME sectors.

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Important Closing Date Note

Take note that applications will not be accepted on the below date and onwards, kindly submit applications ahead of the closing date indicated below.

09/05/26