Mulanga Makhubele

This role is a combined technical and management role and I switch between the two depending on our team priorities. Some weeks I will spend, teaching, supporting, clarifying client requirements and figuring out team organisation while other weeks will be spent digging into analysis, working with our python code base or researching and creating new models for a new feature. I work on everything from Team and project management to writing code, code reviews, new feature research and model building to client data analysis. Giving client presentations on what our product is and answering their questions on what we do and how we work. Stakeholder management, mostly internal but also teaching the internal team how technical messages and timelines need to be communicated to clients. This being a startup I also contribute strategically where necessary. Every now and then all the time I have spent listening to "How I Built This" by Guy Raz on NPR, and the knowledge I have gathered consuming endless books about startups also comes into play.

My primary role is to be a participant in and to lead data science projects, solving a variety of use cases across the Telkom Group and for its' customers. Our teams main objective is to build AI products for the group. Job responsibilities

- Setting yearly objectives for our team and projects that are aligned with our teams strategic objective.

- Advocating for AI in the group and building AI use cases and prototypes that demonstrate the potential value of AI in business processes.

- Engaging with internal customers to firm up their requirements and turn those requirements into project plans.

- Build project roadmaps and manage the execution of the project (the build, test, deployment) and even support.

- Use mathematical, statistical and machine learning techniques to solve problems.

- Program solutions using data science programming languages and analytics frameworks (Python, R, Git, Linux, Keras, Pandas etc.)

- Execute end to end exploratory data analysis and product development processes.

- Implement visualization (Power BI), advanced analytics and data science solutions for customers.

- Use Google Cloud Platform infrastructure e.g (Cloud run, Big Query, AI Notebooks) to scale your hardware or for your CI/CD pipeline.

- Participate in the development of Junior data scientists.

- Work with the data management team to retrieve data from source.

- Provide input on most appropriate data science tools and/or approaches for specific projects.

- Develop and peer review code.