Postbank is a bank by South Africans for South Africans and like all the other renowned commercial banks in the South African market, Postbank is all about serving the South African citizens and creating lasting value. The Bank’s core function is to provide cost-effective financial services to South Africans. It views itself as a banking and financial ser...
Purpose of the Job
- The Senior Business Intelligence (BI) Specialist is responsible for leading the design, development and implementation of approved BI solutions and data-driven insights, in line with company standards and guidelines.
Job Responsibilities
Strategic Input and Resource Planning
- Provide input into Business Intelligence (BI) and Analytics-related strategies, policies and procedures, in line with departmental and company goals.
- Contribute to continuous improvement initiatives, in collaboration with the Analytics team.
- Identify and recommend new BI tools, data visualisation frameworks and technologies to improve scalability, accuracy and accessibility of insights.
- Provide input into BI-related resource and budgetary requirements to support annual planning and project forecasting.
Solution Development and Delivery
- Analyse complex data sets in close collaboration with business units and Analytics team, to identify BI requirements and translate them into project goals and deliverable.
- Manage the full life cycle and solution implementation of approved BI projects.
- Manage resources, delegate responsibilities and provide guidance and support to data analysts to ensure achievement of project goals
- within the allocated budget and timelines
- Lead the development and manage seamless integration of BI data models, semantic layers and reporting structures that promote consistent, accurate and accessible information delivery.
- Track and report on project progress and adherence to budget and timelines.
- Monitor performance and reliability of BI solutions after implementation and identify solutions to address issues or concerns, ensuring operational success and stability.
Data Governance, Compliance and Quality Assurance
- Contribute to the development and manage adherence to data management and governance practices to ensure data quality, integrity and accessibility across analytics systems.
- Monitor compliance with the Protection of Personal Information Act (POPIA), the Financial Sector Conduct Authority (FSCA) requirements, and Postbank’s internal data governance policies.
- Contribute to the development and safeguarding of data dictionaries, and oversee secure storage of datasets, code and analytical outputs in designated repositories, ensuring data hygiene, knowledge retention and reproducibility.
- Review BI data models and datasets for compliance, performance and structural optimisation prior to publication.
- Identify and propose solutions for data-quality issues or concerns, to ensure the integrity and hygiene of data for auditable business reporting.
People Management
- Clarify role expectations, priorities and standards for direct reports through regular review of job profiles.
- Lead the performance cycle for direct reports: set goals, conduct regular performance appraisals / reviews and provide timely feedback.
- Coach and mentor direct reports to build capability and encourage professional growth by recognising achievements, supporting individual development plans, identifying skills gaps and coordinating opportunities for training / learning and development.
- Allocate and balance work, set delivery timeframes, and maintain team capacity through leave management.
- Partner with HR on workforce planning; participate in recruitment, selection, onboarding and probation management.
- Promote a positive, inclusive, respectful team climate that supports wellbeing, safety and constructive collaboration and engagement.
- Oversee adherence to HR policies and South African Labour Legislation in people practices.
- Address performance, conduct and attendance issues promptly; manage grievances and, when necessary, initiate disciplinary steps in line with procedure.
- Encourage continuous improvement and adopt enabling tools and technology that enhance team effectiveness.
Qualifications and Experience
- Bachelor’s degree in computer science, Data Science, Machine Learning, or relevant field (NQF Level 7
- Honours / Masters in relevant field (NQF Level 8 / 9 (Ideal)
- 5+ years of experience in Relevant Business Intelligence-related experience at a specialist level
- 3+ years of experience in Managerial / Team Leading experience
- Relevant experience in the Banking Industry (Advantageous)
Skills and 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.
Phase Target, Skills & Algorithms, Tech Stack Mapping
Core Data &BI Engineering
- Database optimization, automated ETL pipelines, stored procedures. SQL Server (SSMS, SSIS), Power Query
- Advanced data modeling, context filtering, row-level security, cloud deployment. Power BI (DAX), Tableau
- Statistical profiling, macro migration, legacy predictive validation. SAS
Predictive AI & Automation
- Binary classification, feature engineering for upsell/crosssell propensity modeling. Python (scikit-learn, XGBoost), R, SQL Server
- Regression trees, ensemble learning, automated lead generation scoring engines. Python, SQL Server, Power Query Survival analysis, lifetime value (LTV) estimation, NLP for service ticket intent. Python (lifelines, HuggingFace), R, Power BI
Advanced Optimization & Geo
- Location allocation algorithms, spatial clustering, spatial regression. ArcGIS, Python (GeoPandas, PySAL)
- Constrained optimization, attribution modeling, marketing mix modeling (MMM). Python (SciPy.optimize), R
- Bridging deep tech with executive business decisions, setting architectural patterns. Full Ecosystem Transformation
go to method of application »
Purpose of the Job
- The Senior AI and ML Specialist is accountable for leading Postbank’s enterprise AI and machine-learning capability for assigned domains. The role defines AI/ML strategy, standards, governance, responsible-AI controls and MLOps practices, prioritises the AI/ML portfolio, directs the AI and ML Developer, and provides authoritative specialist leadership over high-impact AI/ML solutions that support secure, ethical, auditable and scalable operational decision-making.
Job Responsibilities
AI/ML Strategy, Portfolio and Governance
- Translate Postbank priorities into an AI/ML roadmap, standards and delivery portfolio for assigned domains.
- Prioritise AI/ML initiatives based on strategic value, feasibility, risk, data readiness, regulatory implications, resource availability and operational benefit.
- Define standards for responsible AI, solution design, model development, validation, explainability, deployment, monitoring, security and retirement.
- Advise the Head: Analytics and senior stakeholders on AI opportunities, constraints, risks, investment needs and implementation options
- Evaluate new AI technologies, tools, vendors and platforms and recommend adoption, containment or rejection based on value and risk.
AI/ML Solution Leadership and MLOps
- Lead complex AI/ML, deep-learning, NLP, optimisation, automation or generative-AI initiatives from concept to deployment handover.
- Approve or challenge AI architecture, algorithm choices, MLOps design, testing strategies, monitoring thresholds and integration approaches.
- Coordinate implementation dependencies with technology, BI, automation, data, risk, operations, compliance and business stakeholders.
- Oversee design and maintenance of MLOps practices for secure, scalable, repeatable and auditable AI/ML delivery.
- Present AI/ML findings, solution options, benefits, limitations and risk implications to executive, operational and technical audiences.
Responsible AI, Risk, Compliance and Auditability
- Own AI/ML governance artefacts, model registers, responsible-AI evidence, deployment documentation and monitoring evidence for assigned domains.
- Ensure compliance with POPIA, FSCA requirements, internal data-governance policies, information-security standards and model-risk controls.
- Oversee fairness, bias, explainability, privacy, robustness, security, drift and performance monitoring for AI/ML solutions
- Coordinate audit, assurance, regulatory or internal-control evidence relating to AI/ML solutions.
- Escalate material ethical, operational, security or compliance risks and recommend control improvements.
People, Resource and Capability Leadership
- Lead, allocate and monitor work of AI and ML Developer resources in line with portfolio priorities, quality gates and deadlines.
- Set role expectations, review performance inputs, coach AI engineering capability and identify development needs
- Contribute to recruitment, onboarding, probation input, workforce planning and succession planning for AI/ML roles.
- Manage workload, continuity, leave planning and delivery risk across AI/ML workstreams
- Promote a professional, responsible, secure and innovation-oriented AI delivery culture aligned to Postbank values
Qualifications and Experience
- Bachelor’s degree in Mathematics, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, Statistics, Applied Mathematics, or a related quantitative/technology field (NQF Level 7).
- Honours or Masters degree in AI, machine learning, data science, computer science, analytics or related field (NQF Level 8/9) (Ideal)
- 8+ years Relevant Artificial Intelligence and Machine Learning-related experience at a Specialist level
- 5+ years Managerial / Team Lead experience
- Relevant experience in the Banking Industry (Advantageous)
Skills and 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.
Phase Target, Skills & Algorithms, Tech Stack Mapping
Core Data &BI Engineering
- Database optimization, automated ETL pipelines, stored procedures. SQL Server (SSMS, SSIS), Power Query
- Advanced data modeling, context filtering, row-level security, cloud deployment. Power BI (DAX), Tableau
- Statistical profiling, macro migration, legacy predictive validation. SAS
Predictive AI & Automation
- Binary classification, feature engineering for upsell/crosssell propensity modeling. Python (scikit-learn, XGBoost), R, SQL Server
- Regression trees, ensemble learning, automated lead generation scoring engines. Python, SQL Server, Power Query Survival analysis, lifetime value (LTV) estimation, NLP for service ticket intent. Python (lifelines, HuggingFace), R, Power BI
Advanced Optimization & Geo
- Location allocation algorithms, spatial clustering, spatial regression. ArcGIS, Python (GeoPandas, PySAL)
- Constrained optimization, attribution modeling, marketing mix modeling (MMM). Python (SciPy.optimize), R
- Bridging deep tech with executive business decisions, setting architectural patterns. Full Ecosystem Transformation
go to method of application »
Purpose of the Job
- The Senior Specialist: Advanced Analytics is accountable for leading Postbank’s advanced analytics and data-science capability for assigned enterprise domains. The role defines analytical standards, prioritises and governs the advanced analytics portfolio, translates strategic and regulatory priorities into executable analytics roadmaps, and provides authoritative specialist leadership over high-impact models, data-science solutions, modelrisk controls, stakeholder advisory and the performance delivery of Data Scientist resources.
Job Responsibilities
Advanced Analytics Strategy, Portfolio and Standards
- Translate Postbank priorities into an advanced analytics roadmap, delivery portfolio and standards for assigned domains.
- Prioritise analytical initiatives based on strategic benefit, regulatory need, operational urgency, data readiness, risk and resourcing constraints.
- Define reusable standards for problem framing, data preparation, model development, validation, documentation, monitoring and reporting.
- Advise the Head: Analytics and senior stakeholders on analytics opportunities, trade-offs, dependencies, risks and investment requirement
- Lead the adoption of scalable analytics methods, platforms and ways of work that improve delivery quality and speed.
Enterprise Solution Leadership and Delivery
- Lead complex predictive, prescriptive, segmentation, forecasting, optimisation and machine-learning initiatives from concept to implementation handover.
- Approve analytical design choices, modelling approaches, validation methods, implementation assumptions and business interpretation for high-impact outputs.
- Coordinate cross-functional dependencies with BI, automation, data, technology, risk, operations and business stakeholders.
- Review and challenge Data Scientist outputs to ensure technical quality, business relevance, reproducibility and governance compliance.
- Present complex analytics findings, recommendations and options to executive, operational and technical audiences.
Governance, Risk, Compliance, and Auditability
- Own the advanced analytics model register, documentation standards and evidence requirements for assigned domains.
- Ensure compliance with POPIA, FSCA requirements, Postbank governance frameworks, data-security controls and model-risk practices.
- Oversee model validation, explainability, bias testing, drift monitoring, performance thresholds, version control and retirement criteria
- Coordinate audit, internal control, regulatory or assurance evidence relating to advanced analytics outputs.
- Escalate material risks and recommend control improvements to the Head: Analytics.
People, Resource and Capability Leadership
- Lead, allocate and monitor work of Data Scientist resources in line with portfolio priorities, deadlines and quality standards.
- Set role expectations, review performance inputs, coach technical capability and identify skills-development needs.
- Contribute to workforce planning, recruitment, onboarding, probation input and succession planning for advanced analytics roles.
- Manage workload, delivery risks, leave planning and continuity of critical analytics workstreams.
- Promote a professional, inclusive, high-accountability delivery culture aligned to Postbank values and governance obligations.
Qualifications and Experience
- Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, or relevant field (NQF Level 7)
- Honours / Masters in relevant field (NQF Level 8 /9) (Ideal)
- 8+ years Relevant data science, machine learning and algorithm-related experience at a specialist level
- 5+ years Managerial / Team Leading experience
- Experience in the Banking Industry (Advantageous)
Skills and 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.
Phase Target, Skills & Algorithms, Tech Stack Mapping
Core Data &BI Engineering
- Database optimization, automated ETL pipelines, stored procedures. SQL Server (SSMS, SSIS), Power Query
- Advanced data modeling, context filtering, row-level security, cloud deployment. Power BI (DAX), Tableau
- Statistical profiling, macro migration, legacy predictive validation. SAS
Predictive AI & Automation
- Binary classification, feature engineering for upsell/crosssell propensity modeling. Python (scikit-learn, XGBoost), R, SQL Server
- Regression trees, ensemble learning, automated lead generation scoring engines. Python, SQL Server, Power Query Survival analysis, lifetime value (LTV) estimation, NLP for service ticket intent. Python (lifelines, HuggingFace), R, Power BI
Advanced Optimization & Geo
- Location allocation algorithms, spatial clustering, spatial regression. ArcGIS, Python (GeoPandas, PySAL)
- Constrained optimization, attribution modeling, marketing mix modeling (MMM). Python (SciPy.optimize), R
- Bridging deep tech with executive business decisions, setting architectural patterns. Full Ecosystem Transformation
go to method of application »
Purpose of the Job
- The Data Analyst is responsible for contributing to the development and integration of approved Management Information System (MIS) dashboards and reports through analysing and transforming complex data, in line with company rules and regulations.
Job Responsibilities
Analytics Input and Support
- Contribute to the development, implementation, and continuous improvement of data and analytics-related processes, procedures and operational plans, in line with departmental and company goals.
- Provide input into data requirements, model-design specifications and needs to support enhancement of operational efficiency within the Analytics team.
- Stay abreast of and provide technical advice and guidance on innovative Business Intelligence (BI) tools, trends and new visualisation technologies in the market to promote ongoing innovation.
Data Analysis and Reporting
- Collaborate with the Senior Business Intelligence (BI) Specialist and Analytics teams to execute assigned projects by integrating advanced analytical outputs into reporting deliverables.
- Develop, maintain, and enhance Management Information Systems (MIS) reports, dashboards, and analytical outputs in collaboration with relevant stakeholders, ensuring achievement of project deliverables and objectives.
- Analyse datasets to identify trends, anomalies, and performance insights that support business decision-making.
- Review data to ensure integrity reliability is maintained across systems, escalating and proposing corrective action / solutions for review and obtain approval by the Senior BI Specialist before implementation of corrective actions.
- Support integration and monitor performance of approved reporting and analytical solution implementation.
- Identify and escalate any risks or concerns to the Senior Specialist for review, while proposing and obtaining approval of solutions for implementation.
- Prepare and present analytical findings and visual outputs in business-relevant format, to inform decision-making.
- Recommend improvements to enhance reporting efficiency, data presentation, and information accessibility.
Data Governance, Compliance and Quality Assurance
- Adhere to all data-governance and reporting standards in compliance with the Protection of Personal Information Act (POPIA),
- Financial Sector Conduct Authority (FSCA) requirements, and internal company policies, rules, and standards.
- Perform data-quality checks, validations, and reconciliations to maintain accuracy of reports and datasets.
- Maintain documentation of report structures, datasets, and data transformations in relevant data repositories to promote data hygiene, integrity, and reproducibility.
- Identify data risks, concerns, integrity issues, or compliance concerns to the Senior Business Intelligence (BI) Specialist for review and resolution.
- Support continuous improvement initiatives related to data quality, integrity, and governance frameworks.
Qualifications and Experience
- Bachelor’s degree in Computer Science, Information Technology, Data Science, or a relevant field (NQF Level 7)
- Advanced degree or MBA preferred (Ideal)
- 3+ years of experience as a Data Analyst
- Experience in the Banking Industry (Advantageous))
Skills and 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.
Phase Target, Skills & Algorithms, Tech Stack Mapping
Core Data &BI Engineering
- Database optimization, automated ETL pipelines, stored procedures. SQL Server (SSMS, SSIS), Power Query
- Advanced data modeling, context filtering, row-level security, cloud deployment. Power BI (DAX), Tableau
- Statistical profiling, macro migration, legacy predictive validation. SAS
Predictive AI & Automation
- Binary classification, feature engineering for upsell/crosssell propensity modeling. Python (scikit-learn, XGBoost), R, SQL Server
- Regression trees, ensemble learning, automated lead generation scoring engines. Python, SQL Server, Power Query Survival analysis, lifetime value (LTV) estimation, NLP for service ticket intent. Python (lifelines, HuggingFace), R, Power BI
Advanced Optimization & Geo
- Location allocation algorithms, spatial clustering, spatial regression. ArcGIS, Python (GeoPandas, PySAL)
- Constrained optimization, attribution modeling, marketing mix modeling (MMM). Python (SciPy.optimize), R
- Bridging deep tech with executive business decisions, setting architectural patterns. Full Ecosystem Transformation
go to method of application »
Purpose of the Job
- The Automation Specialist is responsible for leading the design, development and implementation of approved automation solutions and ETL (Extract, Transform, Load) processes, in line with company standards and guidelines.
Job Responsibilities
Strategic Input and Resource Planning
- Provide input into data-automation and analytics strategies, policies and procedures, in line with company and departmental goals
- Contribute to continuous improvement initiatives, in collaboration with the Analytics team
- Provide input into automation-related resource and budgetary requirements to support annual planning and project forecasting
Solution Development and Delivery
- Collaborate with business units, Analytics team members to identify automation requirements and translate them into project objectives and deliverables
- Manage the full life cycle and solution implementation of approved automation projects
- Manage resources, delegate responsibilities and provide guidance and support to direct reports to ensure achievement of project goals within the allocated budget and timelines
- Manage seamless integration of automation frameworks and automated feedback loops between analytical models, reporting systems and operational business units
- Track and report on project progress and adherence to budget and timelines
- Identify and propose solutions to address any concerns or issues to mitigate any potential risks or delays
- Monitor performance of automation solutions after implementation and identify solutions to address issues or concerns, ensuring operational success and stability.
Data Governance, Compliance and Quality Assurance
- Contribute to the development and manage adherence to data management and governance practices to ensure data quality, integrity and accessibility across analytics systems
- Monitor compliance with the Protection of Personal Information Act (POPIA), the Financial Sector Conduct Authority (FSCA) requirements, and Postbank’s internal data governance policies
- Contribute to the development and safeguarding of data dictionaries, and oversee secure storage of datasets, code and analytical outputs in designated repositories, ensuring data hygiene, knowledge retention and reproducibility
- Collaborate with Analytics team members to align automation practices with enterprise data-governance standards and metadata requirements
People Management
- Clarify role expectations, priorities and standards for direct reports through regular review of job profiles
- Lead the performance cycle for direct reports: set goals, conduct regular performance appraisals / reviews and provide timely feedback
- Coach and mentor direct reports to build capability and encourage professional growth by recognising achievements, supporting individual development plans, identifying skills gaps and coordinating opportunities for training / learning and development
- Allocate and balance work, set delivery timeframes, and maintain team capacity through leave management
- Partner with HR on workforce planning; participate in recruitment, selection, onboarding and probation management
- Promote a positive, inclusive, respectful team climate that supports wellbeing, safety and constructive collaboration and engagement
- Oversee adherence to HR policies and South African Labour Legislation in people practices
- Address performance, conduct and attendance issues promptly; manage grievances and, when necessary, initiate disciplinary steps in line with procedure
- Encourage continuous improvement and adopt enabling tools and technology that enhance team effectiveness
Qualifications and Experience
- Bachelor’s degree in Information Technology, Telecommunications, Computer Science or relevant field (NQF Level 7)
- 5+ Years Relevant Automation-related experience at a specialist level
- 3+ Years Managerial / Team Leading experience
- Candidates with relevant experience in the Banking Industry (Advantageous)
Skills and 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.
Phase Target, Skills & Algorithms, Tech Stack Mapping
Core Data &BI Engineering
- Database optimization, automated ETL pipelines, stored procedures. SQL Server (SSMS, SSIS), Power Query
- Advanced data modeling, context filtering, row-level security, cloud deployment. Power BI (DAX), Tableau
- Statistical profiling, macro migration, legacy predictive validation. SAS
Predictive AI & Automation
- Binary classification, feature engineering for upsell/crosssell propensity modeling. Python (scikit-learn, XGBoost), R, SQL Server
- Regression trees, ensemble learning, automated lead generation scoring engines. Python, SQL Server, Power Query Survival analysis, lifetime value (LTV) estimation, NLP for service ticket intent. Python (lifelines, HuggingFace), R, Power BI
Advanced Optimization & Geo
- Location allocation algorithms, spatial clustering, spatial regression. ArcGIS, Python (GeoPandas, PySAL)
- Constrained optimization, attribution modeling, marketing mix modeling (MMM). Python (SciPy.optimize), R
- Bridging deep tech with executive business decisions, setting architectural patterns. Full Ecosystem Transformation
go to method of application »
Purpose of the Job
- The Senior Analytical Cube Developer is responsible for leading the design, development and implementation of approved Advanced Analytical Cube Development solutions, in line with company standards and guidelines.
Job Responsibilities
Strategic Input and Resource Planning
- Provide input into Cube Development and analytics strategies, policies and procedures, in line with company and departmental goals.
- Contribute to continuous improvement initiatives, in collaboration with the Analytics team.
- Provide input into resource, infrastructure and budgetary requirements to support analytical cube projects and data-engineering initiatives.
Solutions Development and Delivery
- Collaborate with business units, Analytics team members to identify cube development and data engineering requirements and translate them into project objectives and deliverables.
- Manage the full life cycle and solution implementation of approved Senior Analytical Cube Development and Data Engineering projects.
- Manage resources, delegate responsibilities and provide guidance and support to direct reports to ensure achievement of project goals within the allocated budget and timelines.
- Manage seamless integration of metadata cube structures, tabular models and related project initiatives of frameworks systems and operational business units.
- Track and report on project progress and adherence to budget and timelines.
- Identify and propose solutions to address any concerns or issues to mitigate any potential risks or delays.
- Monitor performance of solutions after implementation and identify solutions to address issues or concerns, ensuring operational success and stability.
Data Governance, Compliance and Quality Assurance
- Contribute to the development and manage adherence to data management and governance practices to ensure data quality, integrity and accessibility across analytics systems.
- Monitor compliance with the Protection of Personal Information Act (POPIA), the Financial Sector Conduct Authority (FSCA) requirements, and Postbank’s internal data governance policies.
- Contribute to the development and safeguarding of metadata, data quality frameworks, data dictionaries, and oversee secure storage of datasets, code and analytical outputs in designated repositories, ensuring data hygiene, knowledge retention and reproducibility.
- Collaborate with Analytics team members to align Senior Analytical Cube Developer practices with enterprise data-governance standards and metadata requirements.
- Identify and resolve data integrity issues affecting cube outputs and propose corrective action.
People Management
- Clarify role expectations, priorities and standards for direct reports through regular review of job profiles.
- Lead the performance cycle for direct reports: set goals, conduct regular performance appraisals / reviews and provide timely feedback.
- Coach and mentor direct reports to build capability and encourage professional growth by recognising achievements, supporting individual development plans, identifying skills gaps and coordinating opportunities for training / learning and development.
- Allocate and balance work, set delivery timeframes, and maintain team capacity through leave management.
- Partner with HR on workforce planning; participate in recruitment, selection, onboarding and probation management.
- Promote a positive, inclusive, respectful team climate that supports wellbeing, safety and constructive collaboration and engagement.
- Oversee adherence to HR policies and South African Labour Legislation in people practices.
- Address performance, conduct and attendance issues promptly; manage grievances and, when necessary, initiate disciplinary steps in line with procedure.
- Encourage continuous improvement and adopt enabling tools and technology that enhance team effectiveness.
Qualifications and Experience
- Bachelor’s degree in, Computer Science, Information Systems Engineering or relevant field (NQF Level 7)
- Honours or Masters in relevant field (NQF Level 8 / 9) (Ideal)
- 5+ Years Relevant Advanced Analytical Cube Development-related experience at a Specialist level
- 3+ Years Managerial / Team Leading experience
- Candidates with relevant experience in the Banking Industry (Advantageous)
Skills and 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.
Phase Target, Skills & Algorithms, Tech Stack Mapping
Core Data &BI Engineering
- Database optimization, automated ETL pipelines, stored procedures. SQL Server (SSMS, SSIS), Power Query
- Advanced data modeling, context filtering, row-level security, cloud deployment. Power BI (DAX), Tableau
- Statistical profiling, macro migration, legacy predictive validation. SAS
Predictive AI & Automation
- Binary classification, feature engineering for upsell/crosssell propensity modeling. Python (scikit-learn, XGBoost), R, SQL Server
- Regression trees, ensemble learning, automated lead generation scoring engines. Python, SQL Server, Power Query Survival analysis, lifetime value (LTV) estimation, NLP for service ticket intent. Python (lifelines, HuggingFace), R, Power BI
Advanced Optimization & Geo
- Location allocation algorithms, spatial clustering, spatial regression. ArcGIS, Python (GeoPandas, PySAL)
- Constrained optimization, attribution modeling, marketing mix modeling (MMM). Python (SciPy.optimize), R
- Bridging deep tech with executive business decisions, setting architectural patterns. Full Ecosystem Transformation
go to method of application »
Purpose of the Job
- The MIS & Reporting Manager is accountable for leading Postbank’s MIS, reporting and operational analytics capability across assigned enterprise reporting domains. The role translates strategic, regulatory and operational priorities into an integrated MIS and reporting portfolio, defines reporting standards and governance controls, manages a team of eight reporting and analytical resources, and ensures the delivery of accurate, timely, auditable and decision-ready information to executive, regulatory, operational and business stakeholders.
Job Responsibilities
MIS and Reporting Strategy, Portfolio and Standards
- Translate Postbank strategic, operational and regulatory priorities into an integrated MIS and reporting roadmap.
- Own the reporting delivery portfolio across recurring, executive, operational, regulatory and ad hoc reporting streams.
- Define and enforce standards for report design, data definitions, metric ownership, refresh frequency, reconciliation, evidence retention and version control.
- Prioritise reporting requests based on risk, regulatory urgency, business value, operational dependency, resource availability and data readiness.
- Advise the Head: Analytics and senior stakeholders on reporting gaps, risks, dependencies, trends and decision-support requirements.
Enterprise Reporting Delivery and Stakeholder Management
- Lead the design, development, enhancement and delivery of dashboards, scorecards, operational packs, regulatory packs and management reports.
- Translate complex stakeholder requirements into reporting specifications, data logic, definitions, business rules, quality checks and delivery plans.
- Coordinate reporting dependencies with BI, data engineering, automation, operations, risk, finance, compliance and business units.
- Review and approve critical reporting outputs before submission to senior stakeholders or formal governance forums.
- Present insights, exceptions, trends, risks and recommended actions in a clear decision-ready format for technical and non-technical audiences.
Data Governance, Data Quality and Auditability
- Own reporting controls for data lineage, reconciliation, completeness, accuracy, timeliness, reproducibility and evidence retention.
- Ensure compliance with POPIA, FSCA requirements, Postbank data-governance standards, information-security rules and internal control expectations.
- Maintain reporting catalogues, data dictionaries, metric definitions, calculation logic, report ownership matrices and issue logs.
- Oversee investigation and remediation of data-quality defects, reporting discrepancies, control failures and stakeholder escalations.
- Coordinate audit, assurance, internal control and regulatory evidence relating to MIS and reporting outputs.
People, Resource and Performance Management
- Manage a team of eight reporting and analytical resources, including Senior Data Analysts, Data Analysts and MIS / reporting resources.
- Allocate work, set delivery priorities, manage deadlines, monitor workload and ensure continuity of critical reporting processes.
- Set role expectations, conduct performance reviews, coach analytical capability and support individual development plans.
- Participate in recruitment, onboarding, probation input, skills planning, succession planning and team-capacity management.
- Promote a high-accountability, service-oriented, governance-compliant and collaborative reporting culture.
Qualifications and Experience
- Bachelor’s degree in Computer Science, Information Technology, Data Science, Statistics, Business Analytics, Finance, Commerce, or a relevant quantitative/technology field (NQF Level 7).
- Honours or Masters degree in Data Science, Business Analytics, Information Systems, Statistics, Finance, Management, or related field (NQF Level 8/9) (Ideal)
- 8+ Years MIS, reporting, data analytics, BI, operational analytics, regulatory reporting or data-management experience, including ownership of complex cross-functional reporting portfolios
- 5+ Years Managerial, supervisory, technical-lead or portfolio-lead experience over analysts, reporting specialists, BI developers or delivery resources
- Experience in the Banking Industry (Advantageous)
Skills and 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.
Phase Target, Skills & Algorithms, Tech Stack Mapping
Core Data &BI Engineering
- Database optimization, automated ETL pipelines, stored procedures. SQL Server (SSMS, SSIS), Power Query
- Advanced data modeling, context filtering, row-level security, cloud deployment. Power BI (DAX), Tableau
- Statistical profiling, macro migration, legacy predictive validation. SAS
Predictive AI & Automation
- Binary classification, feature engineering for upsell/crosssell propensity modeling. Python (scikit-learn, XGBoost), R, SQL Server
- Regression trees, ensemble learning, automated lead generation scoring engines. Python, SQL Server, Power Query Survival analysis, lifetime value (LTV) estimation, NLP for service ticket intent. Python (lifelines, HuggingFace), R, Power BI
Advanced Optimization & Geo
- Location allocation algorithms, spatial clustering, spatial regression. ArcGIS, Python (GeoPandas, PySAL)
- Constrained optimization, attribution modeling, marketing mix modeling (MMM). Python (SciPy.optimize), R
- Bridging deep tech with executive business decisions, setting architectural patterns. Full Ecosystem Transformation
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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 and 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)
Skills and 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.
Phase Target, Skills & Algorithms, Tech Stack Mapping
Core Data &BI Engineering
- Database optimization, automated ETL pipelines, stored procedures. SQL Server (SSMS, SSIS), Power Query
- Advanced data modeling, context filtering, row-level security, cloud deployment. Power BI (DAX), Tableau
- Statistical profiling, macro migration, legacy predictive validation. SAS
Predictive AI & Automation
- Binary classification, feature engineering for upsell/crosssell propensity modeling. Python (scikit-learn, XGBoost), R, SQL Server
- Regression trees, ensemble learning, automated lead generation scoring engines. Python, SQL Server, Power Query Survival analysis, lifetime value (LTV) estimation, NLP for service ticket intent. Python (lifelines, HuggingFace), R, Power BI
Advanced Optimization & Geo
- Location allocation algorithms, spatial clustering, spatial regression. ArcGIS, Python (GeoPandas, PySAL)
- Constrained optimization, attribution modeling, marketing mix modeling (MMM). Python (SciPy.optimize), R
- Bridging deep tech with executive business decisions, setting architectural patterns. Full Ecosystem Transformation
Method of Application
If you wish to apply and meet the requirements, please forward your Curriculum Vitae (CV) to [email protected] Please indicate in the subject line the position you are applying for. To view the full position specification, log on to www.postbank.co.za and click on Careers.
Interested and qualified? Go to
Postbank (SOC) Ltd on www.postbank.co.za to apply
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