About this role
Standard Bank Group is a leading Africa-focused financial services group that offers career-enhancing opportunities alongside talented professionals. The Data Scientist assists in applying data mining techniques and statistical analysis to large structured and unstructured data sets to understand phenomena and model business problems.
Daily work involves discovering insights and opportunities through statistical, algorithmic, machine learning and visualisation techniques. The role requires working closely with clients, data and technology teams to turn data into critical information used to make sound business decisions.
You will develop and deploy machine learning and statistical models while performing data preprocessing, cleansing and feature engineering. Large datasets are analysed to identify patterns, trends and insights that support credit risk, churn and propensity modelling.
The position provides exposure to banking data, systems and products within an innovative financial services environment. Collaboration across BI, software engineering and project delivery teams supports model deployment and integration into production systems.
Requirements
- 3–4 years’ experience in Data & Analytics / Data Monetisation
- Experience working with structured and unstructured data
- Strong knowledge of data architecture, ETL and data flows
- Experience in data mining and statistical analysis
- Proficiency in SAS, R or Python and visualisation tools (Power BI, Tableau)
- Experience in machine learning modelling and predictive analytics
- Understanding of banking data, systems and products
- Exposure to software engineering, BI and project delivery
Responsibilities
- Develop and deploy machine learning and statistical models to solve business problems
- Perform data preprocessing, cleansing and feature engineering to improve model performance
- Analyse large datasets to identify patterns, trends and insights for decision-making
- Design and maintain data pipelines and ETL processes to support analytics
- Build and maintain predictive models for credit risk, churn and propensity
- Present insights through visualisations and reports to business stakeholders
- Support model deployment and integration into production systems
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