Associate Economic Statistician at South African Reserve Bank

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

• Collect, process, validate, quality-assure, analyse and disseminate monetary and credit statistics in accordance with divisional timelines.
• Compile and contribute to statistical releases, website publications, internal publications and the Quarterly Bulletin.
• Validate the source data received from reporting institutions, including through outlier investigations as well as data mapping and reconciliation processes.
• Apply monetary and financial statistics methodologies and relevant international statistical standards, including the Monetary and Financial Statistics Manual and Compilation Guide of the International Monetary Fund (IMF).
• Support methodological reporting, classification reviews and technical guidance related to monetary and credit aggregates as well as related macroeconomic statistics.
• Participate in projects and initiatives related to the compilation of monetary and credit statistics, including process improvements, system enhancements, data-structure reviews and implementation support.
• Use open-source software and related analytical tools to improve the collection, processing, visualisation and analysis of monetary and credit statistics, including reproducible workflows, dashboards, analytical outputs and supporting documentation.
• Contribute to the quarterly Integrated Economic Accounts and related departmental initiatives through data sourcing, validation and quality assurance.
• Support the seasonal adjustment processes for monetary statistics, including reviewing and updating the seasonally adjusted monetary time series.
• Contribute to the G20 Data Gaps Initiative recommendations that are relevant to monetary and credit statistics, including emerging data needs, potential new data sources, methodological alignment and stakeholder engagement.
• Prepare and deliver briefings, presentations and technical inputs for senior management, internal forums and external stakeholder engagements, including engagements with reporting institutions and industry forums.
• Provide clear, professional and technically sound responses to internal and external data queries, and escalate complex methodological, classification or reporting matters where appropriate.
• Keep abreast of relevant methodological changes, market developments, reporting requirements and international best practice, and assess their implications for monetary and credit compilation.
• Analyse data using business intelligence tools to identify trends and present analytical findings in written reports, including graphs and the Quarterly Bulletin tables.
• Assist with presentations as well as general administrative and ad hoc tasks required by the division.

Qualifications

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

• at least an Honours degree (NQF level 8) in Economics or Statistics, preferably with modules on Accounting, Data Science or Finance; and
• at least 2–5 years of relevant experience in monetary and financial statistics, banking-sector data, macroeconomic statistics, regulatory reporting, economic analysis, financial economics, accounting or a related statistical compilation environment.

The following would be an added advantage:

• the ability to program in R and/or Python. 

Additional requirements include:

• an affinity for statistics compilation and economic analysis, with a strong interest in applying statistical principles to real-world economic data;
• a proven track record in conducting and delivering high-quality economic analyses; 
• proficiency in the use of Microsoft Office products such as Microsoft Word, Excel and PowerPoint, including the ability to use tools (functions and formulas) to organise, analyse and adjust data; 
• knowledge and insight regarding international statistical manuals and best practice, for example the IMF’s Monetary and Financial Statistics Manual and Compilation Guide;
• basic knowledge and understanding of the generic statistical business process model;
• a task-oriented approach, with excellent time management skills to thrive in a deadline-driven environment where work often requires managing pressure while maintaining quality;
• the ability to work independently as well as within a team/project environment;
• strong report-writing skills;
• the ability to present complex statistical data and analyses clearly and concisely;
• taking initiative;
• problem-solving skills;
• excellent communication and interpersonal skills; 
• analytical skills; and 
• keen attention to detail.