Our client – Interfront (a global technology solutions provider that focuses solely on the Customs and Border Management business area) – is looking for 3 Data Scientists to complement the current in-house capacity to meet data management requirements ( data extraction and analysis).
The work will be carried out at SARS’ head office and they will be responsible for, among other things, the following:
Acquire, extract, process and synthesize data sets from SARS systems. Meet specified data standards required for general data requests, specialist data requests as well as ad hoc requests, including analysis of these to provide insights and identify revenue opportunities.
Provide advisory support on big data, data analytics, and data mining techniques and methods to fully utilize data for the benefit of the organization.
- Develop, modify, update and improve the scripts available to improve the extraction methods used.
Assist in the practical implementation of the data management plan.
Degree and experience:
Selected candidates must have the following qualifications and experience.
- Minimum honors degree in a data science related qualification, or
- Relevant/appropriate data science certification
- In-depth knowledge of business information management,
- Highly skilled in advanced analytics and big data
- Relevant knowledge of statistical analysis tools; SQL and SAS
At least 5 years of advanced work experience in data analytics and business intelligence environment
Knowledge of the enterprise data warehouse environment and the creation of data marts.
Experience in managing and working with large datasets.
The results of the exercise can be summarized as follows:
- Automated periodic provision of tax statistics
- Design and development (improvement) of models for the different tax products
- Fulfillment of National Treasury requirements using SSIS software package and other miscellaneous tools as prescribed
Additional output / Ad hoc tasks / General
- Improvements and enhancements to the NRCM server environment, processes to support automation and machine learning features.
- Explore automation features and machine learning techniques to improve data management and analysis processes.
- Data science
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