Founding Engineer
We automate it. Continuous data cleaning, data that stays analysis-ready, and signals across the whole study so sponsors can make decisions on data they trust.
What that means in practice: - Reconciling data from many systems that describe the same patient differently - A rules engine expressive enough that new studies get configured, not coded - Findings a clinician will act on, which means correct and self-explaining - Real product surface: this is what people stare at all day
In production with pharma sponsors. Small team, second engineering hire, no legacy to defend.
Stack: Django/Python, React, AWS. SOC 2 Type II.
Comp: $170-220K + equity.
Skills
- aws
- python
- react
- django
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