Stanbic IBTC Bank is a leading African banking group focused on emerging markets globally. It has been a mainstay of South Africa’s financial system for 150 years, and now spans 16 countries across the African continent.
Standard Bank is a firm believer in technical innovation, to help us guarantee exceptional client service and leading-edge financial solutions. Our growing global success reflects our commitment to the latest solutions, the best people, and a uniquely flexible and vibrant working culture. To help us drive our success into the future, we are looking for resourceful individuals to join our dedicated team at our offices.
- Operations: a range of essential and complex services to ensure processes across the bank work as effectively and efficiently as possible
- Assist in applying data mining techniques and conduct statistical analysis to large, structured and unstructured data sets to understand and analyze phenomena.
- Model business problems, discovering insights and opportunities through statistical, algorithmic, machine learning and visualization techniques, working closely with clients, data and technology teams to turn data into critical information used to make sound business decisions
Key Responsibilities / Accountabilities
- Assist the gathering of data for use in Data Science models, ensuring that chosen datasets best reflect the organization’s goals.
- Assists various mathematical, statistical, and simulation techniques to typically large and unstructured data sets in order to answer critical business questions and create predictive solutions which drive improvement in business outcomes.
- Codes, tests and maintains scientific models and algorithms and identifies trends, patterns, and discrepancies in data and determines additional data needed to support insight.
- Use data profiling and visualization techniques using tools to understand and explain data characteristics that will inform modelling approaches.
- Utilizes the appropriate data storage and data mining tools to ensure value can be extracted from the sourced data
- Supports various mathematical, statistical, and simulation techniques to answer business questions within specific areas of focus. Develops modelling solutions that enable the forecast of quality data outcomes.
- Ensures that volumetric predictions are modelled so that resource requirements are optimally considered. Supporting reporting production ensuring sustainable and effective modelling solutions.
- Supports and implements operational IA plan, rules, methodologies and coding initiatives in order to ensure IA for remediation efforts. Support and implements the strategy for productionalising automation software so that it is accurate and well maintained.
- Provides input into Data management and modelling infrastructure requirements and adheres to the organization’s infrastructure development processes, including the management of User Acceptance Testing (UAT).
- Supports business integration through integrating model outputs into endpoint production systems, incorporating business requirements and knowledge of best practices.
- Assists in building machine learning models from and utilizes distributed data processing and analysis methodologies.
Qualifications and Experience
- First Degree in Information Technology or Information Studies
- Proficiency in application and web development. Structured and Unstructured Query languages e.g. SQL, QlikView; Tableau, Python, C#, Java, C++, HTML
- Minimum of three years proven development experience in software and software engineering
- Understanding of financial services data processes, systems, and products.
- 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 in technical business intelligence.
- Knowledge of IT infrastructure and data principles.
- Project management experience.
- Experience in building models (credit scoring, propensity models, churn, etc.)
- Experience in working with unstructured data (e.g. Streams, images)
- Experience with data visualization tools, such as Power BI, Tableau, etc.
- Experience with common data science toolkits, such as SAS, R, SPSS, etc
Knowledge / Technical Skills / Expertise:
- Diagramming and Modelling
- Data Integrity
- Research and Information Gathering
- Data Analysis
- Knowledge Classification
- Database Administration