Data Scientist - NPS at South African Reserve Bank

Detailed description

The successful candidate will be responsible for the following key performance areas:

• Develop requirements for predictive analytics by developing design specifications (decision models) in line with the data governance. The design specifications include the validation and success criteria, business goals and the business process model involved in making decisions.
• Prepare the required data by performing a data assessment, consolidation and data integrity testing. 
• Identify actionable insights from the prepared data by providing statistics about data features, correlations between features, aggregation of data and the creation of new features. The results of this data exploration must be added to the requirements to focus on the most relevant data.
• Perform predictive modelling (design, create, test and implement hypotheses and analytical models) using prepared data.
• Monitor, measure and report on analytical results to ensure appropriate business recommendations and insights. The analytical results may require an update of the decision requirements model.
• Ensure that there are deliverables resulting from the model development, such as deployed reusable software assets and knowledge transfer that allows business to integrate this asset in their business processes.
• Lead applied analytics initiatives and produce analytical outputs in support of relevant business objectives.
• Research, benchmark, design, implement and validate cutting-edge algorithms/models to analyse diverse sources of data to achieve targeted outcomes and provide expertise on mathematical concepts for the NPSD.
• Create a performance culture within the division, define performance expectations and conduct effective performance management of direct reports.
• Evaluate own performance against given criteria and identify and address task-specific learning needs.
• Plan, organise, control, manage and evaluate the work of team members and administer human capital functions.
• Collate and provide management information for decision-making purposes.

QUALIFICATIONS

Job requirements

To be considered for this position, candidates must be in possession of:

• a Postgraduate degree in Statistics, Mathematics, Engineering, Economics, Computer Science or an equivalent qualification; and seven years’ experience as a data scientist.

Additional requirements include: 

• technical expertise in at least two of the following programming languages: Python, R, SAS, Scala and SQL; 
• technical expertise in statistics and machine learning (ML): regressions, clustering techniques, time series techniques, bagging and boosting trees, ensemble models and neural networks; 
• experience in and working with: 
• descriptive statistics and exploratory data analysis (EDA); 
• large datasets in flat files, relational databases and distributed systems (Hadoop), with some exposure to AWS, Azure and/or GCP (would be an advantage); 
• visualisation tools (e.g. Power BI, SAS, Tableau and MicroStrategy); 
• large volumes of structured and unstructured data and leveraging it to build artificial intelligence (AI)/ML solutions through end-to-end automated data pipelines; and 
• MLOps for AI/ML model deployment monitoring/enhancements for standalone solutions or as part of larger products; 
• ability to communicate complex ideas effectively, both verbally and in writing; and 
• experience in working and collaborating with a variety of stakeholders throughout a data science project’s life cycle.