Application Scoring Specialist Experience Level: Senior (8 years) Join a dynamic, data-driven organisation thats redefining the future of lending and credit analytics across Africa. Youll work with passionate Data Scientists, Analysts, and risk experts who thrive on solving complex problems in low-data environments particularly in the SME sector, where creativity and precision truly matter. This is a hybrid role, perfect for someone who wants to blend deep technical work with strategic influence. Youll design, test, and deploy cutting-edge scorecards that directly impact multi-million-rand lending portfolios. Plus, youll mentor future data talent while shaping the scoring strategy of the future. If youre driven by challenge, collaboration, and making data tell its story, this is your stage. Key Responsibilities: Design and develop robust application scorecards, including reject inference and model validation. Lead feature engineering initiatives that push model accuracy and business value forward. Innovate in data-scarce environments, especially within SME lending. Partner with senior stakeholders to align technical models with strategic goals. Mentor and guide Junior Analysts, fostering a culture of technical excellence. Drive best practices in model governance and deployment. Deliver insights and recommendations to senior leadership in a compelling, story-driven way. Job Experience and Skills Required: Bachelors Degree in Mathematics, Statistics, Actuarial Science, Data Science, or a related field. 8 years of hands-on experience in application scoring and credit risk modelling. Deep expertise in feature engineering, scorecard design, reject inference, and validation. Strong technical proficiency in SAS (required) and Paragon Modeler (advantageous). Track record of developing models across multiple industries (e.g., retail, fintech, telecoms, or insurance). Skilled at working with limited datasets to deliver robust, scalable solutions. Excellent communication skills and the confidence to influence executives. Leadership experience in mentoring, teaching, or developing teams. Preferred Attributes: Experience in SME or alternative credit scoring. Knowledge of PD and behavioural model development. Familiarity with modern data science and machine learning techniques. Comfort in fast-paced, agile, and cross-functional environments. Why Join Us?: Work on high-impact projects that transform the credit and SME lending landscape. Be part of a data team that values innovation, collaboration, and real-world impact. Hybrid flexibility and autonomy to design, lead, and deliver projects your way. Competitive rewards and the chance to influence how credit scoring evolves in emerging markets. Apply now! For more exciting Finance vacancies, please visit:

Were looking for a seasoned Application Scoring Specialist (8 years experience) who thrives at the intersection of data science, credit risk, and business strategy. If you have a strong track record in scorecard development, feature engineering, and reject inference and enjoy mentoring the next generation of Analysts while influencing executive stakeholders, this role is for you. What Youll Do: Lead the design, development, and peer review of application scorecards , including reject inference. Drive feature engineering initiatives to unlock stronger model performance. Bring cross-industry insights to credit decisioning strategies. Innovate in low-data environments (particularly SME lending) with predictive solutions. Mentor and develop Junior Analysts, while influencing senior business leaders. Provide thought leadership in model governance and best practice . Spearhead the development of PD models and contribute to behavioural model enhancements. Present complex technical concepts in clear, strategic terms at executive level. What You Bring: 8 years hands-on experience in application scoring & credit risk modelling. Expertise in scorecard development, reject inference, and model validation . Strong skills in feature engineering and data pre-processing . Proven ability to deliver robust models in data-scarce environments . Proficiency in SAS (essential) and experience with Paragon Modeler (advantageous). A Degree in Mathematics, Statistics, Mathematical Statistics, or Engineering . Strong communication and leadership skillsable to mentor and inspire, but also influence at boardroom level. Preferred Extras: SME lending or alternative credit scoring experience. Familiarity with machine learning in scoring contexts . Experience generating new features for advanced modelling. Agile, cross-functional team experience. If youre passionate about scoring, thrive on solving complex data challenges, and want to influence the future of lending across industries this is your chance. Apply now!