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, working closely 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
Experience
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 visualisation tools, such as Power BI, Tableau, etc.
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.).
Additional Information
Behavioral 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
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