# Lumicity — VP, Data & AI

- Generated: 2026-08-20 1:18 PM EDT
- Canonical posting: https://www.linkedin.com/jobs/view/4455410303/
- Provider: LinkedIn / Lumicity
- Location: Massachusetts, United States; remote with 25% travel
- Employment: Contract-to-hire
- Compensation: Base + bonus + equity; amounts not disclosed
- Posted: LinkedIn displayed “1 day ago” when fetched at 1:13 PM EDT on August 20, 2026; exact posting time unavailable
- Applicants: 83
- Reports to: CTO
- Domain: Life sciences / biotechnology
- Positioning track: Executive leader
- Fit outcome: FAIL — 90% capability coverage, overridden by a hard travel conflict
- Generation decision: No resume, cover letter, or outreach note generated

## Central mandate

Build a new enterprise data, AI, and innovation function; unify fragmented scientific and operational data; migrate legacy infrastructure to a modern cloud platform; establish responsible AI governance; hire the team; and own budget, vendors, and executive communication.

## Evidence map

1. **Build a data/AI function from scratch — direct.** Keith established NorthBay’s AI/ML practice, built IDW’s AI platform and 11-engineer team, and created new data capabilities at TriMark.
2. **Legacy-to-cloud data migration — direct and quantified.** He delivered TriMark’s first AWS data lake across 11 heterogeneous ERP environments in seven months, reducing reporting from about two months to one day.
3. **Unify fragmented multi-source data — direct.** TriMark’s acquired-business ERP consolidation and the Lythos cloud integration platform are direct evidence.
4. **Applied AI/ML leadership and safe deployment — direct.** AssistX supports 70+ automations across 20+ workflows; MassMutual work covered AI governance, privacy, model transparency, bias, drift, and auditability.
5. **Hands-on builder who scales into people leadership — direct.** Keith built initial systems personally and then recruited and led teams of 7, 11, 23–25, and 24 engineers.
6. **Life-sciences / scientific R&D background — direct.** Ph.D. in molecular biology; pharma and bioinformatics experience at Wyeth/Pfizer, Ingenuity Systems, and other scientific-software organizations.
7. **Executive presence, budget, vendors, and build/buy decisions — direct/partial.** Longstanding C-level reporting, business-case, funding, budget, partner, and architecture decision experience; vendor ownership is less explicitly quantified.
8. **Work model and travel — hard conflict.** The posting explicitly requires 25% travel; Keith’s maximum is 5% and fewer than three nights monthly.

## Material gaps and caveats

- Explicit 25% travel is a hard constraint conflict.
- Contract-to-hire rather than a clearly permanent executive appointment.
- Compensation amounts are not disclosed.
- Employer identity is described only as a Massachusetts biotechnology company; Lumicity is the recruiter.

## Full normalized job description

This role is not open to third-party support. Employment is contract-to-hire with base, bonus, and equity. It is remote with 25% travel, reports to the CTO, and serves a life-sciences/biotechnology company.

The VP will establish a new data, AI, and innovation function, including its charter, roadmap, operating model, hiring plan, budget, and vendor strategy. The leader will audit and unify fragmented data across laboratory, research, operational, and legacy systems; lead migration to modern cloud data platforms without disrupting active R&D; set enterprise AI strategy; establish governance for model risk, privacy, IP protection, and responsible use; act as the executive voice for data and AI; and build tooling that provides scientists with trustworthy data.

Required experience includes 10+ years in data or AI leadership; building an early-stage team or function; leading a consequential legacy-to-cloud platform migration; unifying fragmented data; applied AI/ML leadership; hands-on builder capability before scaling into people leadership; a scientific R&D, life-sciences, biotech, or pharma background; and executive presence. Preferred differentiators include lab, research, or clinical systems integration; regulated or IP-sensitive data; and pharma, medical-device, or AgTech R&D data.

## Artifact metadata

- Archived JD capture only; no application PDFs were produced because the role failed a hard fit gate.
- Google Drive used: No