Data Scientist at Rand Water

Job Advert Summary    

• Rand Water is currently looking for a data science specialist who applies advanced analytical, modelling, and technical expertise to analyse and interpret complex datasets, transforming data into meaningful insights that inform decision-making. The role is also responsible for planning, coordinating, and delivering data-driven projects for the FPMO, ensuring they are completed within agreed scope, timelines, and budget. This role exists to assist in optimising the performance of the Finance Programme Management Office. It is the custodian of the unit’s performance management and assists to drive continuous improvement.

Minimum Requirements    

• BCom Degree or equivalent PM Diploma
• Common majors include Computer Science, Statistics, Mathematics, Data Science (if offered)
• PEMBOK/PRINCE 2/ Waterfall/ Agile PM qualification
• Experience
• 3-5 Years of Experience: expected to be proficient in core data science skills and have experience working on complete data science projects. Will lead on small to medium projects and contribute significantly to larger ones.
• Having a portfolio of data science projects and relevant certifications can demonstrate the skills and knowledge, potentially offsetting the need for extensive experience, especially for this level role.

Primary Duties    

• Lead the development and execution of the Finance Business Unit’s data strategy, including data governance, quality, security, and regulatory compliance.
• Drive end-to-end data science initiatives, from problem definition and project planning through to implementation and value delivery.
• Design, develop, and deploy advanced analytical, statistical, and machine learning models to address complex business challenges.
• Analyse large and complex datasets to generate actionable insights that support strategic and operational decision-making.
• Apply strong knowledge of core financial systems and finance-related modules (e.g. ERP systems, general ledger platforms such as SAP and Oracle), including underlying data structures, workflows, and configurations.
• Support and enable the integration of financial systems with other enterprise platforms (e.g. CRM, CaseWare, SAP BPC) using appropriate integration methodologies and tools.
• Communicate analytical insights clearly to both technical and non-technical stakeholders through effective data visualisation and storytelling.
• Collaborate with cross-functional teams to translate business requirements into scalable, data-driven solutions.
• Stay abreast of emerging data science, analytics, and financial systems trends, recommending innovative approaches where appropriate.
• Provide mentorship and technical guidance to junior data scientists and analysts within the Finance function.
• Plan, monitor, and manage data science projects, including scope, timelines, risks, budgets, and quality assurance.
• Build and maintain strong stakeholder relationships through regular engagement, reporting, and presentations.

JOB REQUIREMENTS

• Education/NQF Level
• BCom Degree or equivalent PM Diploma
• Common majors include Computer Science, Statistics, Mathematics, Data Science (if offered)
• PEMBOK/PRINCE

Knowledge    

• Mathematics and Statistics: This is the bedrock of data science. A strong understanding of statistical concepts like hypothesis testing, probability distributions, and linear regression is essential. You should be comfortable working with data, manipulating it statistically, and interpreting the results.
• Programming Languages: Proficiency in at least one programming language is a must. Python is the king in data science, widely used for data analysis, machine learning, and data visualization. Familiarity with SQL is crucial for querying relational databases and retrieving data for analysis. Knowledge of other languages like Java or C is beneficial depending for this role.
• Machine Learning: Understanding core machine learning concepts like decision trees, random forests etc is crucial.
• Data Wrangling and Data Cleaning: Real-world data is often messy and incomplete. Data scientists need to be adept at data cleaning techniques to identify and address errors, missing values, and inconsistencies in the data. Tools like Pandas in Python are commonly used for data manipulation.
• Data Visualization: Data storytelling is a critical aspect of data science. Data scientists need to be able to present their findings through clear and compelling visualizations like charts, graphs, and dashboards. Tools like Tableau, Power BI etc
• Understands relevant project management processes; wider programme/project interdependence and coordination; and when to engage additional support or expertise.
• Knowledge of Projects optimization practices
• Financial Systems: knowledge of core financial systems and functionalities (e.g., ERP systems with finance modules, general ledger systems eg. SAP, Oracle). This includes understanding data structures, workflows, and configuration options
• Systems Integration: Knowledge of integration methodologies and tools for connecting various financial systems with other enterprise systems (e.g., CRM, CaseWare, SAP BPC).

Skills    

• Technical Skills:
• Math & Statistics.
• Programming Languages
• Machine Learning & Deep Learning
• Data Wrangling & Cleaning
• Data Visualization
• Communication
• Critical Thinking & Problem-Solving
• Teamwork & Collaboration
• Continuous Learning

Attitude    

• Analytical Thinking and Judgement
• Results Orientation
• Stakeholder Engagement and Influence
• Communication and Data Storytelling
• Collaboration and Teamwork
• Adaptability and Learning Agility
• Professionalism and Ethical Conduct
• Planning, Organisation, and Accountability
• Innovation and Continuous Improvement
• Coaching and Capability Development

Closing Date    
2026/02/12