Quant Programming & Research Engineering

Replacing Python loops with array thinking - the single highest-leverage skill for research code that is both corr

How quants prove their code is right: analytic checks, boundary cases, property-based invariants, and tolerances that re

A result you cannot reproduce is not a result. Seeds, environments, version control, and logged experiments turn lucky r

The Pragmatic Programmer’s core habits - don’t repeat knowledge, decouple components, and shoot tracer

Measure before you optimize. Then vectorize the hot path - and understand why a compiled, statically-typed languag

Where quant work really lives: clean data flowing through reliable stages, queried with SQL, and promoted from a noteboo