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(1842) Associate Economic Statistician
Fa Evra Saasfaprod1 · Pretoria, South Africa
About The Role
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.
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.
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