We are a central Data Science team that are part of the Future Planning & Resilience directorate and Organisational Performance Management department. We collaborate with our colleagues across the organisation on a wide range of projects, such as finance, water, energy, urban waste, transport, safey and securty, health, and more. We use data and our technical skills to provide insights and reduce uncertainty, to help the organisation focus their actions and ultimately benefit Cape Town residents and industries.
To establish, promote and mature an analytics-driven culture to generate insights that can be used by the organisation to inform strategic and operational decisions and ultimately benefit the residents of Cape Town
To design, develop and implement data infrastructures, pipelines, platforms and products to enable data functions for the organisation and ultimately benefit the residents of Cape Town
Everyone in the Data Science team has areas that they excel at, and areas where they need development. While we organise ourselves into specialised roles according to our job title and strengths, we expect that everyone is able to understand and minimally perform the job of all the other roles in the team.
We do this because:
- We can all pitch in when there's an 'all hands on deck' problem to be solved
- Each role can structure their work such that it is easier for the other roles to integrate
- It keeps us tightly knit
- It avoids boredom
All members of the unit know how to create and execute a computer script, construct a presentation for a layperson audience, present well to senior leadership, and explain to anyone who will listen why a pie chart is a bad idea.
When it comes to data science products, the team is encouraged to test and try out new ideas and approaches, even if they may fail. We value innovation, risk-taking and continuous improvement. This does not mean you are left to your own devices. New ideas and prototypes are presented to the team and constructive criticism provided, which help improve the data product, processes and outcomes. Mistakes are seen as opportunities for learning and growth, rather than failures. The goal is to continuously improve. This means that employees are encouraged to learn from their experiments, and to use that knowledge to iterate and improve upon their ideas over time.
We use open source technologies, for which we are grateful, and try and contribute to the community where we can. To date we have not come across an organisational problem that cannot be solved with open source technologies. This enables us to be flexible and agile to deliver on stakeholders needs and not be constraint by procurement challenges.
We are open and transparent about our development process, with project plans, code, and documentation available for anyone to view and contribute to. This creates a culture of openness and honesty that encourages trust and fosters innovation.
The Data Analytics/Science landscape and open source projects are constantly evolving and improving, which requires team members to stay up-to-date with new technologies and best practices. This creates a culture of continuous learning, where team members are encouraged to develop their skills and share their knowledge with others.
- Data Scientist
- Data Analyst
(1 vacancy) - Front End Developer (Data)
(1 vacancy)