Prototyping

The goal of a prototyping project is to answer a feasibility question without committing to full development. Building a complete solution takes time and resources. A prototype makes it possible to test the core idea quickly and decide whether to invest further, change direction, or stop.

The daily work involves scoping the question the prototype should answer, choosing a simple approach that can be built quickly, building the prototype, and presenting results to stakeholders. A prototype does not need to handle all edge cases or be maintainable by others; it needs to be good enough to answer the feasibility question.

The main tools are Python for building models and scripts, and visualisation tools like matplotlib or Streamlit for presenting results. SQL is used to extract the data needed for testing. The focus is on speed and simplicity rather than production code quality.

Prototyping projects are common in organisations that are exploring new capabilities or deciding whether to invest in a new approach. The work connects closely to the Data Scientist and Business Analyst roles. It appears across all sectors but is especially common in technology, consultancy, and financial services.