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Company Description
Standard Bank Group is a foremost financial services group focused on Africa, and an innovative entity on the international scene, that provides an assortment of opportunities for career advancement—alongside the opportunity to work with some of the industry's most talented, driven professionals. Our clientele varies from individuals, businesses of all sizes, wealthy families, and large multinational corporates and institutions. We are fervently dedicated to facilitating growth in Africa. Delivering genuine, substantial value to our clients and the communities we engage, and creating a genuine sense of purpose for you.
Job Description
Oversee data mining techniques and conduct statistical analysis to large, structured and unstructured datasets to understand and analyze phenomena. Model intricate business issues, discover insights and opportunities through statistical, algorithmic, machine learning and visualization techniques, working closely with clients, data and technology teams to transform data into crucial information used to make informed business decisions. Oversee predictive modeling.
- Acts as a subject matter expert from a data science perspective and provides input into all decisions relating to data science and its use. Educate the organization on data science perspectives on new approaches, such as testing hypotheses and statistical validation of results. Validates and certifies the work of other data scientists and trains team members in statistical models and guides junior colleagues or less experienced staff on projects and drives leading practice.
- Builds machine learning models from and utilizes distributed data processing and analysis methodologies. Competent in Machine Learning programming in R or Python, with supplementary skill in Matlab, Java, etc. Familiar with the Hadoop distributed computational platform, including the broader ecosystem of tools such as HDFS / Spark / Kafka.
- Codes, tests, and maintains scientific models and algorithms; identifies trends, patterns, and discrepancies in data; and determines additional data needed to support insight. Processes, cleanses, and verifies the integrity of data used for analysis.
- Develops, implements, monitors and maintains a comprehensive operational IA plan, rules, methodologies, and coding initiatives in order to drive IA for remediation efforts. Develops and coordinates a comprehensive strategy for productionalizing automation software so that it is accurate and well maintained.
Qualifications
Minimum Qualifications
Type of Qualification: Post Graduate Degree
Field of Study: Information Technology
Type of Qualification: Post Graduate Diploma
Field of Study: Information Studies
Experience Required
Data Monetization
Data & Analytics
8-10 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.
8-10 years
Proven development experience in software / software engineering. Up to date with developments in IA field. Experience in technical business intelligence; in-depth understanding of the bank's data processes, systems, and products. Knowledge of IT infrastructure and data principles forming the basis for data quality management. Project management experience. Exposure to data governance and regulatory matters. Experience in building models (credit scoring, propensity models, churn, etc)
Additional Information
Behavioral Competencies:
- Adopting Practical Approaches
- Articulating Information
- Challenging Ideas
- Checking Details
- Examining Information
- Exploring Possibilities
- Interacting with People
- Interpreting Data
- Meeting Timescales
- Producing Output
- Providing Insights
- Team Working
Technical Competencies:
- Data Analysis
- Data Integrity
- Database Administration
- Knowledge Classification
- Research & Information Gathering
