Lead Bioinformatics Scientist, Genomics Pipelines

Caris MPI, Inc.

Phoenix (AZ)

On-site

USD 120,000 - 180,000

Full time

6 days ago
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Job summary

Caris Life Sciences is seeking a Staff Bioinformatics Scientist in Phoenix to lead a team developing and validating NGS bioinformatics pipelines in a clinical/translational genomics setting. You will partner with lab, software, IT, quality, and scientific teams to deliver reliable analytical solutions and ensure regulatory compliance.

The role emphasizes technical leadership, project management, and scalable workflow implementation while staying current with emerging genomic analysis methods.

Qualifications

  • PhD in a related field and strong bioinformatics background.
  • 5–8 years hands-on bioinformatics with NGS pipelines.
  • 2–4 years of people leadership and project coordination.
  • Proficiency in Python/Bash/SQL/R; cloud experience.
  • Experience with AWS and regulated environments is preferred.

Responsibilities

  • Lead, coach, mentor, and develop a team of bioinformatics scientists.
  • Manage day-to-day bioinformatics operations and ensure timely delivery.
  • Establish project plans, priorities, and resource allocations.
  • Oversee development and validation of NGS pipelines and workflows.
  • Support end-to-end genomic data analysis and reporting workflows.
  • Drive scalable, automated computational workflows and best practices.

Skills

Bioinformatics
Leadership
Python
Bash
SQL
R
Cloud computing
Communication

Education

PhD or equivalent in related field

Tools

AWS

Job description

Caris Life Sciences is seeking a Staff Bioinformatics Scientist in Phoenix to lead a team developing and validating NGS bioinformatics pipelines in a clinical/translational genomics setting. You will partner with lab, software, IT, quality, and scientific teams to deliver reliable analytical solutions and ensure regulatory compliance.

The role emphasizes technical leadership, project management, and scalable workflow implementation while staying current with emerging genomic analysis methods.

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