Company Description

Standard Bank Group is a leading Africa-focused financial services group, and an innovative player on the global stage, that offers a variety of career-enhancing opportunities – plus the chance to work alongside some of the sector’s most talented, motivated professionals. Our clients range from individuals, to businesses of all sizes, high net worth families and large multinational corporates and institutions. We’re passionate about creating growth in Africa. Bringing true, meaningful value to our clients and the communities we serve and creating a real sense of purpose for you.

Job Description

Apply data mining techniqes 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.

Builds machine learning models from and utilises distributed data processing and analysis methodologies. Competent in Machine Learning programming in R or Python, with supplementary still in Matlab, Java, etc. Familiar with the Hadoop distributed computational platform, including broader ecosystem of tools such as HDFS / Spark / Kafka.Provides input into Data management and modelling infrastructure requirements and adheres to the organisations infrastructure development processes, including the management of User Acceptance Testing (UAT). Conducts regression testing across all relevant systems as required.Ensure business integration through integrating model outputs into end-point production systems, where requirements must be understood and adopted relating to data collection, integration and retention requirements incorporating business requirements and knowledge of best practices.Acts as a subject matter expert from a data science perspective and provides input into all decisions relating to data science and the use thereof. Educate the organisation on data science perspectives on new approaches, such as testing hypotheses and statistical validation of results. Ensure ongoing knowledge of industry standards as well as best practice and identify gaps between these definitions/data elements and organisation data elements/definitions.Directs the gathering of data for use in Data Science models, ensuring that chosen datasets best reflect the organisations goals. Performs data pre-processing including data manipulation, transformation, normalisation, standardisation, visualisation and derivation of new variables/features. Utilises advanced data analytics and mining techniques to analyse data, assessing data validity and usability; reviews data results to ensure accuracy and communicates results to Stakeholders.

QualificationsFirst Degree in Information Technology, Information studies or related from a recognised InstitutionPost Graduate Degree in Information Technology, Information studies is preferred.Proficiency in application and web development. Structured and Unstructured Query languages e.g. SQL, Qlikview; Tableau; SSIS SSRS, Python JSON , C#, Java, C++, HTML1-2 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.).3-5 years experience 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. 

Additional Information

Technical Competencies:

Data AnalysisData IntegrityDatabase AdministrationDiagramming & ModellingResearch and Information GatheringKnowledge Classification

Behavioural Competencies:

Articulating InformationDirecting PeopleDocumenting FactsEmbracing ChangeEstablishing RapportInteracting with PeopleMaking DecisionsManaging Tasks