Scientific Data Operations Lead

Digitailor

South San Francisco (CA)

On-site

USD 110,000 - 160,000

Full time

3 days ago
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Job summary

Axiom is seeking an Operations Lead to own the end-to-end delivery of scientific data programs that power AI models for drug safety and discovery. You will coordinate across internal teams and partner laboratories, manage capacity and timelines, and ensure data integrity through rigorous reconciliation of samples and metadata.

Ideal candidates have strong program management skills, experience in biotech or similar settings, and a passion for building scalable processes that improve throughput

Qualifications

  • Experience coordinating complex programs across multiple teams and external partners.
  • Strong data analysis and problem-solving abilities.
  • Familiarity with SOPs, documentation, and escalation processes.

Responsibilities

  • Own operational delivery of data programs across internal teams and partner laboratories.
  • Coordinate data generation, capacity, timelines, and handoffs from planning through validated data delivery.
  • Protect data integrity by reconciling compound identities, sample histories, and experimental metadata.
  • Build scalable operating systems using trackers, dashboards, SOPs, alerts, and AI agents to automate coordination.
  • Communicate with pharmaceutical customers, AI research partners, laboratories, and internal teams to align expectations and delivery.

Skills

Analytical thinking
Cross-functional collaboration
Program management

Tools

SQL
Python
Dashboards
Spreadsheets

Job description

Axiom is seeking an Operations Lead to own the end-to-end delivery of scientific data programs that power AI models for drug safety and discovery. You will coordinate across internal teams and partner laboratories, manage capacity and timelines, and ensure data integrity through rigorous reconciliation of samples and metadata.

Ideal candidates have strong program management skills, experience in biotech or similar settings, and a passion for building scalable processes that improve throughput

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