Reporting to the Chief Digital Officer, the incumbent will be responsible for the application of data science and advanced quantitative methods, which include machine learning, deep learning, artificial intelligence, predictive analytics to enable key strategic, tactical, and operational use-cases within the domain of water, electricity, and infrastructure management – as per company Digital Strategic Framework. Responsible for the end-to-end data Lifecyle – from strategic planning, data collection, through monitoring, evaluation, and incremental improvement
THE CANDIDATE PROFILE
- Ability to communicate with executives and senior management across sectors (company, local government, government, and industry)
- Basic understanding of finance and human capital management processes
- Project Management
- Problem solving and analytical
- Diligence
- Good business judgment
- Result and self-driven
- Good communication skills
- Self-direction and eagerness to learn
- Independent worker
- Strong time-management skills
- The ability to work on multiple projects for multiple stakeholders
- The ability to mentor and provide guidance for other team members
- A systems approach to thinking, as opposed to a siloed the candidate needs to understand how their work affects the greater system.
- The ability to work without supervision and take accountability for the work they deliver
- The ability to liaise with a client, sifting through the fluff and extracting the actual requirements
QUALIFICATION AND EXPERIENCE
- Support the Chief Digital Officer and Senior Data Architect using a variety of state-of-the-art cloud-based technologies to solve data analysis and prediction problems
- Identify and act on new opportunities for data driven business in data science and analytics
- Recognise when existing solutions can be generalised to solve new problems and address new data-as-a-service verticals
- Work in a collaborative environment developing data science methods, tools, and algorithms to solve problems
- Become fluent in analytical modelling using company’s internal data modelling platforms and tool.
- Continuously learn and apply latest and fit-for-purpose, open-source and proprietary tools and technologies to achieve results, including some or all of the following
Cloud
- Microsoft Azure (must)
- AWS
- Google Cloud
Big Data
- Mondodb
- Hadoop
- Cassandra
Machine Learning
- Kubeflow
- Tensorflow
- PyTorch
Analytics and visualisation
- Microsoft PowerBi (must)
- Microsoft Excel (must)
- Google Charts
Languages
- Python (must)
- R (must)
- SQL (must)
- Associated tools and technologies as they become available, and the platform evolves
- Load and merge data originating from diverse sources
- Performa data cleansing, and quality management
- Pre-process and Transform data for model building and analysis
- Troubleshoot data quality issues and work with team members to reach solutions
- Perform descriptive analytics to discover trend and pattern in the data
- Create visualizations, including dashboards to provide insights on large data sets and input to finished reports
- Develop predictive models for business solution
- Deploy predictive and other models to production
- Analyse output products to assure data quality and conformance to requirements
- Develop technical specification for 3rd party platform data integration and streaming
- Participate in continuous improvement efforts to increase available data quality and speed of delivery
- Address ad-hoc domain-specific data analytic requirements from domain or cluster leaders; and a continuously deliver user-centric data visualization’s, publications, and products
Desired Skills:
- Problem solving and analytical
- Result and self-driven
- Good communication skills