Apply data mining techniques and conduct statistical analysis to large, structured and unstructured data sets to understand and analyse phenomena. Model complex business problems, discovering insights and opportunities through statistical, algorithmic, machine learning and visualisation techniques, workingclosely with clients, data and technology teams to turn data into critical information used to make sound business decisions. Execute intelligent automation and predictive modelling.
Qualifications
- Completed Matric
- Information Studies Degree
- Information Technology Degree
- Proficiency in application and web development. Structured and Unstructured Query languages e.g. SQL, Qlikview; Tableau; SSIS SSRS, Python JSON , C#, Java, C++, HTML
Experience
- 5 – 7 years Proven development experience in software and software engineering. Understanding of financial services data processes, systems, and products. Experience in technical business intelligence. Knowledge of IT infrastructure and data principles. Project management experience. Exposure to governance and regulatory matters as it relates to data. Experience in building models (credit scoring, propensity models, churn, etc.).
- 5 – 7 years’ Experience in working with unstructured data (e.g. Streams, images) Understanding of data flows, data architecture, ETL and processing of structured and unstructured data. Using data mining to discover new patterns from large datasets. Implement standard and proprietary algorithms for handling and processing data. Experience with common data science toolkits, such as SAS, R, SPSS, etc. Experience with data visualization tools, such as Power BI, Tableau, etc.
Additional Information
Behavioural Competencies
- Adopting Practical Approaches
- Articulating Information
- Challenging Ideas
- Examining Information
- Exploring Possibilities
Technical Competencies
- Data Analysis
- Database Administration
- Data Integrity
- Knowledge Classification
- Research & Information Gathering
