Manager Quantitative Analytics

Business Segment: Business & Commercial Banking
Location: ZA, GP, Johannesburg, Baker Street 30
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
Qualifications
Information Studies or Information Technology DegreeProficiency in application and web developmentStructured and Unstructured Query languages e.g. SQL, Qlikview; Tableau; SSIS SSRS, Python JSON , C#, Java, C++, HTMLExperience
5-7 years proven development experience in software and software engineeringExperience in technical business intelligence and Project management experienceExposure to governance and regulatory matters as it relates to data and Experience in building models (credit scoring, propensity models, churn, etc.)5-7 years experience in working with unstructured data (e.g. Streams, images)Experience with data visualisation tools, such as Power BI, Tableau, etc and Experience with common data science toolkits, such as SAS, R, SPSS, etc Additional Information Adopting Practical ApproachesArticulating InformationChallenging IdeasExamining InformationUnderstanding of financial services data processes, systems, and productsKnowledge of IT infrastructure and data principlesUnderstanding of data flows, data architecture, ETL and processing of structured and unstructured dataUsing data mining to discover new patterns from large datasetsImplement standard and proprietary algorithms for handling and processing dataPlease note: All our recruitment processes comply with the applicable local laws and regulations. We will never ask for money or any from of payment as part of our recruitment process. If you experience this, please contact our Fraud line on +27 800222050 or ******
#J-18808-Ljbffr