Data Scientist

Postbank (SOC) Ltd; Pretoria; On-site; ZAR 900,000 - 1,300,000; Full time

Job summary

South African Postbank SOC Limited is seeking a Data Scientist to independently design, develop, validate and operationalise advanced analytics and machine-learning solutions across business problem areas. You will translate regulatory questions into analytical approaches while ensuring auditable, production-ready outputs for decision-making.

Responsibilities include end-to-end analytics, data preparation, model risk governance, and stakeholder advisory.

Qualifications

• Bachelor’s degree in Mathematics, Statistics, Applied Mathematics, Data Science, Engineering, Economics, or a related quantitative field (NQF Level 7).
• Honours or Masters degree in a quantitative, data science, analytics or related field (NQF Level 8/9 (Ideal)).
• 5+ Years Relevant data science, machine learning and algorithm-related experience at a specialist level.
• Experience in the Banking Industry (Advantageous).

Responsibilities

• Own assigned advanced analytics workstreams from problem framing to deployment-ready output.
• Translate business problems into analytical hypotheses, data requirements, modelling approaches and delivery plans.
• Design and build statistical, machine-learning and optimisation models using appropriate techniques and documented assumptions.
• Determine suitable validation, back-testing and monitoring approaches for assigned models and analytical outputs.
• Convert model and analysis results into clear business recommendations, implementation options and risk considerations for stakeholders.
• Acquire, integrate, profile and transform structured and unstructured data from approved sources.
• Design repeatable data preparation, feature engineering and analytical pipelines with appropriate quality controls.
• Maintain version-controlled code, model artefacts, assumptions, metadata, outputs and documentation for auditability and knowledge retention.
• Identify data-quality, lineage, completeness and integrity issues and recommend corrective actions to the Senior Specialist.
• Engage business, operations, BI, automation, data and technology stakeholders to clarify requirements and implementation constraints.
• Present analytical findings to technical and non-technical audiences in a clear, evidence-based manner.
• Provide specialist input into analytics standards, reusable methods, reusable code libraries and continuous-improvement initiatives.
• Guide junior analysts or project contributors on technical methods where required, without formal people-management accountability.

Education

Bachelor’s degree in Mathematics, Statistics, Applied Mathematics, Data Science, Engineering, Economics, or a related quantitative field (NQF Level 7)

Honours or Masters degree in a quantitative, data science, analytics or related field (NQF Level 8/9)

5+ Years Relevant data science, machine learning and algorithm-related experience at a specialist level

Experience in the Banking Industry (Advantageous)

Job description

Purpose of the Job:

The Data Scientist is accountable for independently designing, developing, validating and operationalising advanced analytics and machine-learning solutions for assigned business problem areas. The role translates complex business and regulatory questions into analytical approaches, makes interpretive technical decisions within approved governance frameworks, and produces auditable, production-ready analytical outputs that support operational, customer, financial, risk and regulatory decision-making across Postbank.

Job Responsibilities:

Advanced Analytics Solution Ownership

• Own assigned advanced analytics workstreams from problem framing to deployment-ready output.
• Translate business problems into analytical hypotheses, data requirements, modelling approaches and delivery plans.
• Design and build statistical, machine-learning and optimisation models using appropriate techniques and documented assumptions.
• Determine suitable validation, back-testing and monitoring approaches for assigned models and analytical outputs.
• Convert model and analysis results into clear business recommendations, implementation options and risk considerations for stakeholders.

Data Engineering, Quality and Reproducibility

• Acquire, integrate, profile and transform structured and unstructured data from approved sources.
• Design repeatable data preparation, feature engineering and analytical pipelines with appropriate quality controls.
• Maintain version-controlled code, model artefacts, assumptions, metadata, outputs and documentation for auditability and knowledge retention.
• Identify data-quality, lineage, completeness and integrity issues and recommend corrective actions to the Senior Specialist.

Model Risk, Governance and Compliance

• Apply Postbank data-governance, model-risk, POPIA, FSCA and internal information-security requirements.
• Conduct reasonableness checks, bias/variance assessments, explainability reviews and performance monitoring for assigned analytical outputs.
• Document model limitations, residual risks and recommended monitoring controls before implementation or handover.
• Support internal reviews, audit requests and regulatory evidence packs relating to analytical models and outputs.

Stakeholder Advisory and Delivery

• Engage business, operations, BI, automation, data and technology stakeholders to clarify requirements and implementation constraints.
• Present analytical findings to technical and non-technical audiences in a clear, evidence-based manner.
• Provide specialist input into analytics standards, reusable methods, reusable code libraries and continuous-improvement initiatives.
• Guide junior analysts or project contributors on technical methods where required, without formal people-management accountability.

Qualifications & Experience:

• Bachelor’s degree in Mathematics, Statistics, Applied Mathematics, Data Science, Engineering, Economics, or a related quantitative field (NQF Level 7).
• Honours or Masters degree in a quantitative, data science, analytics or related field (NQF Level 8/9 (Ideal)
• 5+ Years Relevant data science, machine learning and algorithm-related experience at a specialist level
• Experience in the Banking Industry (Advantageous)

Data Analytics Capability Roadmap:

A phased skills pathway for strengthening data engineering, business intelligence, predictive AI, automation, optimisation and strategic analytics capability.

Phase 1: Core Data & BI Engineering

• Data Pipeline Modernization: Database optimization, automated ETL pipelines and stored procedures.
• Advanced Business Intelligence: Advanced data modeling, context filtering, row-level security and cloud deployment.
• Enterprise Analytics Legacy Integration: Statistical profiling, macro migration and legacy predictive validation.

Phase 2: Predictive AI & Automation

• Behavioral Modeling & Marketing AI: Binary classification and feature engineering for upsell/cross-sell propensity modeling.
• Lead Automation & Income Estimation: Regression trees, ensemble learning and automated lead generation scoring engines.
• Customer Service & Retention AI: Survival analysis, lifetime value estimation and NLP for service ticket intent.

Phase 3: Advanced Optimization & Geo

• Spatial Network Optimization: Location allocation algorithms, spatial clustering and spatial regression.
• Marketing & Media Mix Optimization: Constrained optimization, attribution modeling and marketing mix modeling.
• Strategic Leadership & Architecture: Bridging deep technical capability with executive business decision-making and architecture patterns.

Skills & Attributes:

• Uncompromising integrity, honesty, and professional ethics.
• Respectful and professional conduct at all times.
• Strong personal accountability and ownership.
• A commitment to excellence in every deliverable.
• High levels of resilience and perseverance when facing obstacles.
• Self-motivation and the ability to operate independently.
• Continuous learning and intellectual curiosity.
• Loyalty to team objectives and organisational success.

Closing date: 16 September 2026

Disclaimers:

The South African Postbank SOC Limited is committed to the achievement and maintenance of diversity and equity in employment, especially with regard to race, gender and disability. In compliance with the bank’s employment equity plans, we encourage and welcome applications from diverse groups from the South African Employee active population. Correspondence will be limited to short-listed candidates only.

If you do not hear from the South African Postbank SOC Limited or its Agent within 3 months of this advertisement, please accept that your application has been unsuccessful. The South African Postbank SOC Limited reserves the right not to fill the positions or to re-advertise the positions at any time.

POPIA provides that everyone has the right to privacy and it includes a right to protection against the unlawful collection, retention, dissemination and use of personal information. By applying for employment you consent to the processing of your personal information with Postbank. Your personal information and any attached text or documentation are retained by Postbank for a period in accordance with relevant data legislation.