PBT Group is seeking three experienced Data Scientists (Mid-Level to Senior) to join a high-performing data and analytics team focused on driving credit risk, lending, and business performance decisions through advanced analytics and predictive modelling.
This opportunity is ideal for Data Scientists with strong experience in the credit industry, particularly in scorecard development, risk modelling, predictive analytics, and data-driven decision making.
Successful candidates will work within a modern cloud-based analytics environment, leveraging Python, SQL, Google Cloud Platform (GCP), BigQuery, and advanced statistical techniques to build and deploy predictive models that support business growth across multiple African markets.
The senior-level position requires deep credit risk expertise and proven experience developing and implementing credit scorecards within lending or financial services environments.
This is an initial 12-month contract with a strong intention of converting to permanent employment thereafter.
Key Responsibilities
Data Science & Predictive Analytics
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Build, deploy, and maintain predictive models supporting credit risk, customer behaviour, collections, and business optimisation initiatives.
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Develop, validate, and monitor credit scorecards and risk models.
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Perform exploratory data analysis to identify trends, patterns, and opportunities within large and complex datasets.
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Apply statistical modelling, machine learning, and advanced analytical techniques to solve business challenges.
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Design and implement feature engineering processes to improve model performance and predictive power.
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Monitor model stability, drift, and performance over time.
Credit Risk Analytics
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Develop and enhance credit risk scorecards and decisioning models.
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Support lending and credit strategies through data-driven insights and recommendations.
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Analyse portfolio performance and customer behaviour to improve risk management practices.
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Collaborate with business stakeholders to translate lending and credit objectives into analytical solutions.
Data Analysis & Reporting
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Extract, transform, and analyse data from multiple sources using SQL and Python.
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Develop dashboards, reports, and visualisations to communicate insights effectively.
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Present analytical findings and recommendations to both technical and non-technical stakeholders.
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Support business performance analysis, customer segmentation, and operational optimisation initiatives.
Stakeholder Engagement
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Collaborate with Data Engineers, Analysts, Product Teams, Credit Teams, and Executive stakeholders.
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Translate business requirements into analytical frameworks and modelling approaches.
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Provide guidance and support to business users on data-driven decision-making.
Data Governance & Best Practice
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Ensure compliance with data governance standards, privacy regulations, and internal controls.
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Maintain documentation relating to models, assumptions, methodologies, and analytical outputs.
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Contribute to the continuous improvement of analytics methodologies and modelling frameworks.
Required Skills & Experience
Essential Experience
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3+ years' experience (Mid-Level) or 5+ years' experience (Senior) as a Data Scientist, Credit Risk Analyst, Quantitative Analyst, or similar role.
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Proven experience developing predictive models within a commercial environment.
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Strong credit industry experience.
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Hands-on experience developing and maintaining credit scorecards.
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Experience working with large-scale datasets and analytical environments.
Technical Skills
Non-Negotiable
Data Science & Analytics
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Predictive Modelling
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Machine Learning
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Statistical Analysis
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Feature Engineering
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Model Validation
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Scorecard Development
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Data Mining
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Exploratory Data Analysis
Cloud & Data Platforms
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Google Cloud Platform (GCP)
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BigQuery
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Google Colab
Data Visualisation
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Looker Studio
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Power BI (advantageous)
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Tableau (advantageous)
Additional Technologies
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Git
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Jupyter Notebooks
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Advanced Excel
Highly Advantageous Experience
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Credit Risk Modelling
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Retail Lending
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Consumer Finance
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Financial Services
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Banking
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Collections Analytics
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Behavioural Scorecards
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Application Scorecards
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IFRS9 Exposure
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Model Governance
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African lending environments
Qualifications
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Bachelor's Degree in:
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Mathematics
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Statistics
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Data Science
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Computer Science
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Actuarial Science
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Engineering
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Related quantitative discipline
Preferred
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Honours or Master's Degree
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Advanced Analytics, Machine Learning, or Credit Risk certifications
Key Competencies
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Strong analytical thinking
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Advanced problem-solving capability
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Commercial acumen
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Strong communication and presentation skills
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Ability to explain complex analytical concepts to business stakeholders
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Curiosity and continuous learning mindset
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Adaptability within fast-paced environments
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Strong collaboration and stakeholder engagement skills
Environment & Culture
This opportunity offers exposure to one of Africa's most data-driven lending environments.
The team consists of highly capable, entrepreneurial professionals who value innovation, collaboration, ownership, and analytical excellence. Candidates should be comfortable operating in a fast-moving environment where initiative and independent thinking are encouraged.
Regular travel opportunities across Africa may form part of the role.
- In order to comply with the POPI Act, for future career opportunities, we require your permission to maintain your personal details on our database. By completing and returning this form you give PBT your consent
- If you have not received any feedback after 2 weeks, please consider you application as unsuccessful.
