profession file · read as its task mix
mostly shared ground
Data scientist
statistics, artificial intelligence
Data scientists frame business questions as testable problems, build models, run experiments and explain what the results mean for a decision. AI now automates much of the model fitting, feature work and write-ups, shifting the role toward problem framing and checking that the answers hold.
The exposed part of the week
// tasks in this mix that sit in machine territory or moving fast
The part that gains value
// the shared and human ground in this job's mix
The full mix
// what fills this job's week ( ●●● core · ●● regular · ● occasional )
Safer ground: build these
// the future skills that shield this particular mix
Critical thinking
reasoning independently, informed by evidence
AI literacy
understand how ai would affect us, for better or worse
Systems thinking
seeing patterns & creating models to handle complexity
Data
collecting, interpreting & processing of stats & info
Math & logic
calculating, quantifying & using logic
Cause & effect
understanding & defining symptoms & underlying problems
Ask yourself
Home fields
// the dossier(s) behind this profession
