Senior Specialist: Data Analytics (Senior Data Scientist) Fixed Term Contract needed at The South African Revenue Service

Job Purpose

• To be responsible for importing, cleansing, transforming, validating, aggregating and analysing data from various sources with the purpose of making conclusions about industry trends and best practices. Develop implementation plans and give advice on data analytics strategies in order to achieve business objectives.

Education and Experience

Minimum Qualification & Experience Required 

• Honours / Postgraduate Diploma (NQF 8) preferably in Statistics, Mathematics, Engineering, Computer Science, Data Science, or related qualification AND 10-12 years’ experience in Data Analytics environment, of which 3-4 years specialist level.  ** Qualifications in Data Science, Machine Learning, or Business Analytics can also be an added advantage *

Alternative #

• Bachelor’s Degree /Advanced Diploma (NQF 7) preferably in Statistics, Mathematics, Engineering, Computer Science, Data Science, or related qualification AND 12 – 15 years related experience in a Data Analytics environment, of which 3-4 years specialist level. 

Minimum Functional Requirements

• Demonstrated experience in Data science / Machine Learning / Artificial Intelligence
• (i.e., have operationalised at least one Machine Learning / Artificial Intelligence project into production from design to deployment).
• Expert technical expertise (certifications, years of experience, portfolio of work) regarding the end-to-end machine learning lifecycle.
• Advanced applied knowledge of, and experience with Data tools and platforms (SQL or equivalent, etc.), programming (SQL, R, Python, etc.).
• Expert applied knowledge (certifications, years of experience, portfolio of work) of statistics and experience using statistical packages for analysing datasets (Excel, SPSS, SAS, R etc.).
• Basic Data warehouse, Data Visualisation, and Business Intelligence knowledge is essential.
• Experience mentoring model builders and ensuring best practices in model development and deployment.
• Demonstrated experience in leading teams of data scientists and machine learning specialists in the design, development, and deployment of machine learning models is highly advantageous.

Job Outputs:

Process

• Analyse and make recommendations about improvements to specialist systems, procedures, policies and practices.
• Proactively identify interconnected problems, determine its impact and use to develop best fit alternatives, developing best practice solutions.
• Recommend changes to optimise processes, systems, practice areas and associated procedures and execute the implementation of change and innovation.
• Influence and communicate across business areas impacted by practice area to minimise resistance and ensure on-boarding of new thinking.
• Integrate business information, compare, analyse and produce reports to identify trends, discrepancies and inconsistencies for decision making purposes.
• Draw on own technical or professional expertise, knowledge and experience to identify and recommend tactical solutions to defined problems in practices.
• Note potential problems and obstacles, accumulate supporting data and initiate actions to prevent or overcome predicted problems as may be identified.
• Constantly monitor the integrity and quality of data and processes to identify deficiencies and facilitate improvement.
• Review the effectiveness of related approaches and methodologies by conducting research, and best practice benchmarking initiatives.
• Conduct assessments and use information to advise, make recommendations and facilitate improvement.
• Communicate the results of their analysis and findings by using basic data visualisation techniques with both internal and external customers.
• To research best practices and support the development of the solutions and recommendations for the current business operations

Governance

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

People

• Provide specialist know-how, support, advice and leadership in area of expertise

Finance

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

Client

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

Behavioural competencies

• Thought Leadership and curiosity
• Accountability – Manages and influences organisational practices in a responsible and dedicated manner.
• Adaptability – Adapts tactics.
• Analytical Thinking – Makes complex plans or analyses.
• Attention to Detail – Drives the policy framework.
• Commitment to Continuous Learning – Links knowledge to current user needs.
• Diversity Awareness – Describes how to influence cultures.
• Fairness and Transparency – Integration. Leads and directs people or groups of recognized specialists.
• Honesty and Integrity – Creates an environment where integrity, honesty and accountability flourish.
• Organisational Awareness – Navigates organisational culture and practices towards organisational effectiveness.
• Problem Solving and Analysis – Tactical analysis. 
• Respect – Collaboration and integration.
•  Trust – Promotes the image of the organisation in terms of good standing.

Technical competencies

• Database Design Management
• Data Collection and Analysis, Machine Learning, Predictive Modelling, Data Visualization, and Big Data Technologies.)
• Machine Learning Model Development: Mastery in building, validating, and operationalising machine learning models, with experience in both supervised and unsupervised learning techniques.
• Operationalisation of Models: Proven ability to transition models from prototype to production, ensuring scalability, reliability and business impact.
• Business Knowledge
• Data Analysis
• Creative and Innovative thinking
• Efficiency improvement
• Functional Policies and Procedures
• Information Management
• Policy Development
• Reporting
• Data Analytics and Computational Modelling
• Data Analytics through the use of statistical and computational techniques and tools.