Research: Machine Learning Data Scientist x3 (9864) needed at The South African Revenue Service

Job Purpose

• To provide expert advice and guidance in the design, implementation and validation of statistical machine learning / artificial intelligence products, be innovative in blending algorithms with the expertise of the organisation, to best serve the needs of SARS customers and support the organisation’s strategic intent of voluntary compliance. Use algorithms to improve operational efficiencies as well as detect non-compliance, conduct research and keep abreast of latest tools and models to be applied in resolving the organisation’s problems.

Education and Experience

Minimum Qualification & Experience Required

• Honours / Postgraduate Diploma (NQF 8) in a quantitative field e.g. Actuarial Science, Statistics, Physics, Computer Science, Data Science, Machine Learning or similar AND 10-12 years’ experience in a similar environment of which 3-4 years at a specialist level

OR

• Bachelor’s Degree / Advanced Diploma (NQF 7) in a quantitative field e.g. Actuarial Science, Statistics, Physics, Computer Science, Data Science, Machine Learning or similar AND 12-15 years related experience of which 3-4 at a specialist level
• A Master’s degree would be advantageous.

Minimum Functional Requirements

• Skilled in statistics or machine learning.
• Able to read and digest academic papers to think creatively about our data and provide guidance on what to build.
• Fluency in a coding language such as R, Python or similar.
• Excellent written and verbal communication. Able to articulate concepts effectively in different ways dependent on the audience – non-technical, non-ML technical, ML/DS practitioners.
• Advanced level of experience with relational databases and SQL knowledge (5+ years).
• Some experience with non-relational databases e.g. DynamoDB (1+ years).
• Experience with different data format types e.g. JSON, Parquet, CSV, Pickle, XML (2+ years).
• Some experience with unstructured data and NLP techniques is desirable (not only ChatGPT e.g. Spacy, Hugging Face) (1+ year).
• Intermediate experience running end-to-end machine learning or research projects (must have been involved in operationalizing ML / AI projects).
• Experience with streaming data is an advantage.
• Cloud experience on AWS, Azure, GCP, IBM Cloud is an advantage.
• Experience with foundational models (deploying as-is, using RAG or fine tuning) is an advantage.

Job Outputs:

Process

• Analyse and make recommendations about improvements to specialist systems, procedures, policies and practices.
• Develop multiple practices in alignment with operational policy and procedural frameworks, supporting tactical development and excellence.
• Integrate business information, compare, analyse and produce reports to identify trends, discrepancies and inconsistencies for decision-making purposes.
• Stay up to date with DS/ML/AI techniques and trends and supporting architecture trends in the domain.
• Think creatively about the organisations’ data and provide guidance on what to build (using skills and innovative mindset to spot opportunities).
• Share best practices and learnings to the team and the wider data specialists across the organisation.
• Analyse and critique Machine Learning models of teammates to continuously improve our artefacts.
• Expose Machine Learning outputs via APIs or similar, to stakeholders to use.
• Define and build dashboards and analyses/reports that track KPIs, experiments and new initiatives.

Governance

• Develop and/or align governance and compliance policies in own practice areas to identify and manage risk exposure liability.

People

• Integrate new knowledge and transfer skills attained through formal and informal learning opportunities in the execution of your job.
• Provide specialist expertise, support, advice and practice thought leadership in area of expertise.

Finance

• Implement and monitor financial control, management of costs and corporate governance in area of specialisation

Client

• Participate in the specialist practice community and contribute positively to organisation knowledge management.
• Develop and ensure implementation of own practices to build delivery excellence, encouraging others to provide exceptional stakeholder service.
• Provide authoritative, specialist expertise and advice to internal and external stakeholders