Job Description

Key Responsibilities:

oDesign and train machine learning models, perform feature engineering and model selection, develop reproducible and modular machine learning pipelines, integrate models into real-time and batch processing architectures, deploy models to production environments, monitor and evaluate model performance post-deployment, package models for stakeholder-facing platforms, and document the full model lifecycle.
oDesign, implement, and maintain CI/CD pipelines, automate model training workflows, implement robust version control, establish audit trails, and automate logging systems
oTransform complex machine learning outputs and statistical findings.
oEnsure compliance with institutional and national data protection policies, particularly POPIA, apply fairness and bias-mitigation techniques, evaluate and document model explainability using tools such as SHAP, LIME, develop and maintain ethical impact assessments (EIAs), promote responsible AI education and awareness.
oEnsure comprehensive, relevant, and accurate operational, management, and statutory reports are available, support ad-hoc reporting and exploratory analysis requests
oEngage stakeholders across multiple institutional domains, facilitate co-design sessions and discovery workshops, act as a liaison between technical teams and business units, document solution requirements, and support stakeholder capacity-building.
oExemplify and promote the BIS core values in the BIS Service Charter.

Requirements:

Qualification: Master's in Data Science, Computer Science, Information Engineering, Mathematical Statistics, or equivalent
Experience: Minimum of 3 years in AI/ML engineering, data science, or analytics roles

Essential Skills:

oProficient in Python, SQL, and model development libraries (scikit-learn, XGBoost, pandas)
oExperience deploying models using Flask, FastAPI, or similar
oFamiliar with Docker, Git, MLflow, Airflow, or other MLOps tools
oStrong grasp of model evaluation, bias detection, and interpretability
oSolid understanding of enterprise architecture, APIs, and data security standards
oExperience in programming PL/SQL, SQL, Python, Oracle Analytics Cloud (OAC), SAP Business Objects, and PowerBI
oExperience in data visualization and communication of results to diverse audiences
oContribute to the creation and maintenance of dashboards, reports, and forecasts for internal users and external stakeholders
oHigh level of analytics, interpersonal, verbal, and written communication skills.
oUtilize statistical techniques for data analysis and provide insights into university processes and performance
oParticipate in the development of data standards and procedures within the analytics team
oCollaborate with senior analysts to identify and prioritize analytical projects that support decision-making processes
oTraining and Support to end-users on how to access and utilize reports and dashboards and develop and maintain documentation on reports, documentation and data processes.

Preferences:

oUnderstanding of University Academic Structure and systems
oUnderstanding of University data.

Detailed Description

Job Requirements

Additional Details

How To Apply

Please note that applications have to be done through iRecruitment only. No hardcopies or emails should be submitted.

Please submit a covering letter for the post, and a detailed CV with names, addresses, contact numbers and e-mail addresses of 3 referees.

By submitting an application for this post the Applicant acknowledges that their personal information will be processed by the University. The Applicant, by their conduct in proceeding with an application for this position, gives their consent to the processing of their personal information as required by the University's Recruitment, Selection and Appointment Policy. Such processing includes logging their information on the University's recruitment systems and disclosing their personal information to University employees identified to take part in the selection and recruitment process. The Applicant consents to any further processing of their personal information as may be required for relevant verification and reference check purposes. The confidentiality of the Applicant's personal information will be maintained.

Closing Date: 30 November 2025

The University is committed to employment equity. Preference may be given to appointable applicants from the underrepresented designated groups in terms of the relevant employment equity plans and policies of the University. The University retains the right not to make an appointment and to verify all information provided by candidates.

Please note that correspondence will only be entered into with shortlisted candidates. The University reserves the right not to make an appointment or to re-advertise.





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