Director, AI-Driven In Silico Data Ops (Remote)

Violet Research Institute; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Violet Research Institute (VRI) is building the future of personalized medicine, combining startup urgency with mission-driven openness. We seek a senior leader to own data infrastructure, LIMS, and AI-native workflows, guiding a cross-disciplinary bioinformatics team across CROs and internal platforms.

You’ll work remotely across the United States, reporting to a senior director, with scope to manage data scientists over time and align experimental and computational programs with shared data

Qualifications

• PhD in computational biology, bioinformatics, biostatistics, computer science or closely related field.
• 7+ years in computational biology, bioinformatics, or data science within biotech/drug discovery.
• Hands-on experience building data infrastructure in a resource-constrained org.
• Comfort with nucleic acid design space (ASO/siRNA).
• Fluency with cloud data platforms (GCP, AWS) and bioinformatics workflow tools.

Responsibilities

• Own LIMS path forward: fix or replace with Benchling or Dotmatics.
• Direct data infrastructure standards for raw assay data and CRO deliverables.
• Lead AI-native workflows for data analysis and literature synthesis.
• Direct the bioinformatics team and ensure outputs meet standards.
• Ensure CRO data quality and align with Wet Lab ops.

Skills

Systems thinking

Computational biology

Bioinformatics

AI-native mindset

Education

PhD in computational biology, bioinformatics, biostatistics, CS

Tools

Benchling

Dotmatics

GCP

AWS

Job description

Violet Research Institute (VRI) is building the future of personalized medicine, combining startup urgency with mission-driven openness. We seek a senior leader to own data infrastructure, LIMS, and AI-native workflows, guiding a cross-disciplinary bioinformatics team across CROs and internal platforms.

You’ll work remotely across the United States, reporting to a senior director, with scope to manage data scientists over time and align experimental and computational programs with shared data