Bioinformatics Manager
$150,000–$150,000 year
RemoteUnited States
Job Summary
Guide and mentor a senior bioinformatics team, defining strategic direction for genomic data pipelines that support broader product and scientific goals. Partner with product and engineering leaders to align technical execution with real outcomes, while bringing structure to project planning and tracking. Represent the function at the leadership level to communicate priorities and tradeoffs, and play a key role in hiring and shaping the team's growth. Translate biological insights into production-grade tools while keeping the group aligned with evolving standards in the genomics space. This role focuses on shaping a core function that feeds directly into tools used across large research and clinical ecosystems, addressing applied problems in rare disease, cancer, and infectious disease within a flexible, remote-first environment.
Required Qualifications
- Experience leading technical teams, including the real-world parts: feedback, performance management, and navigating team dynamics.
- Ability to explain complex bioinformatics concepts to both technical and non-technical stakeholders without losing clarity.
- Strong grounding in genomics and data analysis, with enough depth to challenge ideas and guide direction.
- Familiarity with common genomics data formats (e.g., sequencing reads and variants) and the tooling ecosystem around them.
- Comfort working with scripting or programming languages (Python, R, or similar) to review work and support technical decisions.
- Exposure to cloud or high-performance computing environments, especially in the context of reproducible pipelines.
- A strategic lens—you can prioritize, scope, and connect technical work to real outcomes.
- Several years of hands-on bioinformatics experience, particularly with next-generation sequencing workflows at scale.
- Advanced academic training in a relevant field, or equivalent practical experience.
- Must be authorized to work in Canada.
Desired Qualifications
- Time spent in startup or high-growth environments.
- Experience exploring and visualizing large-scale biological datasets.
- Familiarity with public genomics resources and integrating diverse data sources.
- Awareness of modern data standards and interoperability practices in genomics.
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