R

Approach

How I work through a problem.

The methods I use and the tools I rely on, in roughly the order I reach for them.

Toolkit

Programming

  • Python
  • C++
  • SQL
  • TypeScript
  • MATLAB

Data & BI

  • Tableau
  • Power BI
  • DBeaver
  • pandas
  • NumPy

AI & ML

  • YOLOv8
  • scikit-learn
  • PyTorch
  • Edge AI
  • Smart sensors

Ways of working

  • Agile (Scrum)
  • Project management
  • Stakeholder communication
  • Analytical writing

Method

  1. 01 · Define the decision

    Begin with the decision the analysis must support. Without a decision in mind, there is no analysis worth running.

  2. 02 · Profile the data

    Examine shape, volume, freshness and gaps. Understand what the data is before deciding what it should say.

  3. 03 · Run the smallest useful experiment

    Choose the cheapest test that could disprove the hypothesis. Speed of feedback compounds faster than cleverness.

  4. 04 · Hand it off cleanly

    Document assumptions, write SQL that reads naturally, and leave tests behind. The next maintainer is as much a stakeholder as the first reader.

  5. 05 · Close the loop

    Report what was decided, not only what was learned. Verify whether the decision held and update the model of the world accordingly.