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Old Mutual Limited in Cape Town, Western Cape, South Africa, is seeking an experienced data analytics professional to turn data into actionable insights for business partners. The role focuses on end-to-end analytics solutions, data acquisition, exploration, and visualization, with applied statistics and machine learning when required.
The ideal candidate will have business acumen, strong analytical thinking, model-building experience, and the ability to communicate insights effectively to
Old Mutual is a firm believer in the African opportunity and our diverse talent reflects this.
Job Description
You will form part of the Mass Foundation Cluster which is one of the largest customer-facing business segments in Old Mutual. Our vision is to be our customers' most trusted financial partner, passionate about helping them achieve their lifetime goals. Our mission is to enable positive futures for our customers, by bridging the gap between their resources and their financial service’s needs. Our primary goal is to facilitate access to financial solutions for our customers and to keep pace with their changing needs. Our target market is the low and emerging-middle income segment.
This role is responsible for turning data into actionable insights for business partners. The role focusses on delivering insight and will also be responsible for creating end to end solutions which includes problem definition, data acquisition, data exploration and visualization, experimenting with statistical and machine learning methods when required, implementing statistical models or solutions where appropriate and providing business with the required insights. The incumbent is individually accountable for achieving results over periods of 3 to 12 months.
Key Result Areas
Turning data into actionable insight for our business partners is what the Customer Experience Analytics team does. We are relentlessly curious and use our advanced analytical skills, tools and platforms to present data as information and create analytical solutions that are interactive and easy to understand.
To deliver insights you will be responsible for creating end to end solutions which includes problem definition, data acquisition, data exploration and visualization, experimenting with statistical methods when required, implementing statistical models or solutions where appropriate and providing business with the required insights.
The ideal candidate will have sound business acumen, analytical thinking skills with modelling experience and the ability to communicate key insights to business in an effective and easy to understand manner.
Data Analysis
Database structures.
Data extraction, manipulation and maintenance (SQL, R, SAS, Excel, Python).
Advanced Analytics
Statistical analysis and predictive modelling (R, Data Robot, SAS Enterprise Miner, Alteryx, SPSS, Python).
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Coaches/ Mentors junior data scientists in the areas of machine learning, statistical analysis and building predictive models.
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions through the use of advanced analytics.
Develop advanced analytics data driven solutions to difficult business problems.
Personal Effectiveness
Accepts and lives the company values.
Accountable for service delivery through own efforts.
Collaborates effectively with others to achieve personal results.
Individually accountable for managing own time, tasks and output quality over periods of up to a year.
Makes increased contributions by broadening individual skills.
Desire to continually research and learn (new technologies, tools, techniques, platforms).
Excellent communicating and presenting skills (written and verbal)
Ability to work under pressure in a fast paced and dynamic environment.
Great at building individual, team and partner relationships.
Qualifications and experience:
Relevant tertiary/post- graduate qualification in statistics or another advanced analytics related field.
5 - 8 years’ work experience of which at least 5 years must be in an advanced analytics type role with model building experience.
End to end experience and understanding of data analytics.
Database structures.
Data extraction, manipulation and maintenance (SQL, R, SAS, Excel, Python).
Statistical analysis and predictive modelling (R, Data Robot, SAS Enterprise Miner, Alteryx, SPSS, Python).
Some experience with R, AWS, Amazon SageMaker or Azure Machine Learning will be beneficial.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Skills
Business Insight
Drives Results
Manages Ambiguity
Manages Complexity
Plans and Aligns
Situational Adaptability
Strategic Mindset
Education
NQF Level 7 - Degree, Advance Diploma or Postgraduate Certificate or equivalent
Closing Date
04 September 2026 , 23:59
_ The appointment will be made from the designated group in line with the Employment Equity Plan of Old Mutual South Africa and the specific business unit in question. _
Old Mutual South Africa is a leading pan-African financial services group providing diverse financial solutions to enhance the lives of customers across 14 countries for over 170 years.
Company size 10,001+ employees
Company type Public company
Total funding 0
Momentum
Momentum
6% in 12 mo
18,007 employees on LinkedIn
Capital
Footprint
107 Rivonia Road, Sandton, Gauteng 2196, ZA Jan Smuts Drive, Pinelands, Cape Town, Western Cape 7405, ZA
Company Old Mutual Limited
Location Cape Town, Western Cape, South Africa