Job Details
- Status
- Active
- Category
- Posted
- Jun 9, 2026
- Expires
- Sep 7, 2026
- Work style
- On-site
About the Role
Lets Write Africa's Story Together!
Old Mutual is a firm believer in the African opportunity and our diverse talent reflects this.
Job Description
naCollect, analyse, report, and interpret data for use in the development of business strategies and tactics and in subsequent appraisal of results. OML Roles mapped to this profile are: People Data & Analytics Practitioner.
Key Responsibilities
Collect, clean, and validate data from multiple sources to ensure accuracy and reliability.
Analyze large datasets to identify patterns, trends, and correlations.
Develop and implement predictive models using statistical and machine learning techniques.
Apply machine learning algorithms for classification, regression, clustering, and forecasting.
Create data visualizations, dashboards, and automated reports (Power BI / Excel).
Collaborate with business stakeholders to translate data into actionable insights.
Support data governance, quality, and compliance initiatives (aligned to DMP / DCAM principles).
Automate data pipelines and workflows where possible.
Perform data profiling, transformation, and feature engineering.
Monitor model performance and continuously improve models.
Minimum Requirements:
Technical Skills
Programming Languages
Python
R
Microsoft SQL (T-SQL)
DAX
TypeScript
C/C++
Ballerina
C# (.NET)
Node.js
Data Tools & Technologies
Power BI
Microsoft Excel (Advanced)
SQL Server / Databases
Jupyter / Notebooks
Power Platform
VS Code
Experience with big data frameworks such as Hadoop
Machine Learning & Analytics
Strong knowledge of:
Supervised & Unsupervised Learning
Predictive Modeling
Statistical Analysis
Data Mining
Data Management & Engineering Skills
Data quality management and validation techniques
Data governance awareness (policies, standards, compliance)
Data profiling and metadata management
ETL / ELT processes
Data security and privacy principles
Non-Technical Skills
Critical Thinking: Ability to analyze complex problems and develop effective solutions.
Communication: Strong ability to explain technical insights to non-technical stakeholders.
Collaboration: Work effectively across teams (IT, business, data owners).
Business Acumen: Understand business processes and translate data into strategy.
Attention to Detail: Ensuring accuracy and reliability of models and reports.
Qualifications
Bachelor’s Degree in Computer Science / Data Science / Statistics (NQF Level 7)
Honours Degree in Computer Science / Data Science (NQF Level 8) will be an advantage.
Experience (Recommended Addition)
1–3+ years in Data Science.
Experience working with large datasets and real-world business problems.
Experience in financial services or insurance.
Skills
Action Planning, Application Development, Business Requirements Analysis, Computer Literacy, Data Compilation, Data Controls, Data Management, Data Modeling, Executing Plans, Gap Analysis, IT Network Security, Management Reporting, Market Analysis, Policies & Procedures, User Requirements Documentation
Competencies
Action Oriented
Collaborates
Cultivates Innovation
Customer Focus
Drives Engagement
Drives Results
Manages Ambiguity
Manages Complexity
Education
NQF Level 7 - Degree, Advance Diploma or Postgraduate Certificate or equivalent
Closing Date
22 June 2026 , 23:59
The Old Mutual Story!
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