Intermediate Data Scientist

7 months ago


Pretoria, South Africa Interfront SOC Ltd. Full time

The successful applicant will join a team of specialist to work together with the current internal capacity at the client on various projects. The work shall be done at the head office of SARS and they will be responsible for, amongst others, the following:

- Acquire, extract, process and synthesise datasets from SARS's systems. Meeting specified data standards required for general data requests, specialised data requests as well as ad hoc requests including analysis thereof to provide insights and identify revenue opportunities.
- Provide advisory support on data analytics, predictive modeling as well as data mining techniques in order to fully utilise data to the benefit of the organisation.
- Develop, amend, update and enhance available scripts to improve the extraction methods used.
- Assist with the practical implementation of the identified machine learning model techniques.

**Qualification and experience**:

- Minimum Honours degree in a Data Science related qualification, or
- Relevant/ Appropriate certification in Data Science
- Advanced knowledge of business information management,
- Highly skilled in advanced analytics and big data
- Relevant knowledge of statistical analysis tools; SQL, SAS, STATA
- Relevant knowledge of programming languages like python to wrangle and clean datasets.
- At least 5 years advanced working experience in data analytics and business intelligence environment
- Knowledge of the enterprise data warehouse environment and creation of data marts.
- Experience in managing and using large data sets.

**The output of the exercise is summarised as follows**:

- Exploring patterns in behavior in the tax base to identify fraudulent and noncompliance.
- Design, development and deploying of models for the prediction of submission and payment of tax products
- Experience in data analysis and methods of supplementing datasets utilized in machine learning modeling.
- Utilizing both supervised and unsupervised machine modeling techniques.
- Outlier detection models to identify noncompliance or tax declaration omissions.

Additional Output / Ad hoc tasks / General
- Improvements and enhancements to the data store, processes to accommodate automation and Machine Learning modeling deployment.
- Explore automation functions and machine learning techniques to improve the data management and analysis processes.


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