Principal Scientist, Translational Lead

Role Summary

We are seeking a dynamic, scientifically rigorous Principal Scientist, Translational Lead to drive translational strategy and execution across early-stage clinical programs. This cross-functional role combines biological insight, data fluency, and operational pragmatism, ideally suited for a candidate with a strong translational medicine background who is also comfortable performing hands-on analytics and drafting infrastructure requirements.

Responsibilities

• Drive translational strategy for early-phase clinical programs, incorporating biomarker hypotheses, patient selection, and endpoint optimization.
• Serve as the lead for biomarker components in clinical protocols, IND submissions, and regulatory engagements.
• Align translational goals with key clinical milestones and trial objectives.
• Design and execute analysis plans for high-dimensional datasets including flow cytometry, RNA-seq, single-cell, and spatial omics.
• Lead integration of molecular and clinical data to uncover pharmacodynamic signals, stratification markers, and mechanisms of resistance.
• Automate and analyze complex flow cytometry and CyTOF datasets using tools such as FlowJo, R (e.g., flowCore, CytoML, ggcyto), or Python-based pipelines.
• Apply modern statistical and machine learning methods to uncover actionable insights, ensuring analytic reproducibility and compliance.
• Contribute to governance meetings, internal reviews, and external scientific communications (e.g., manuscripts, abstracts).
• Provide thought leadership at the interface of clinical development and translational science.
• Evaluate new biomarker platforms and external datasets to expand translational capabilities.
• Mentor junior scientists and cultivate a high-performing, collaborative translational culture.

Qualifications

• PhD in Bioinformatics, Computational Biology, Immunology, Molecular Biology, or related discipline.
• 8+ years of industry experience in translational medicine, biomarkers, or bioinformatics in oncology, immunology, or rare disease.
• Proficiency in automated flow cytometry analysis, including multicolor panel data interpretation and integration with other biomarker modalities.
• Hands-on fluency in R and/or Python for statistical modeling, data visualization, and reproducible bioinformatics.
• Demonstrated ability to design and execute translational analysis plans and influence clinical development.
• Experience contributing to INDs or regulatory filings involving biomarker or flow cytometry data.
• Familiarity with early-phase trials in cell therapy, immuno-oncology, or engineered therapeutics.
• Experience working in GCP/GxP-regulated environments or defining analytics/compliance workflows.
• Exposure to tools such as FlowJo, Cytobank, Spectre, or Bioconductor-based cytometry packages.
• Background in small biotech or matrixed R&D settings with high execution ownership.

Skills

• Biomarker discovery and translational data integration
• High-dimensional data analysis (flow cytometry, transcriptomics, proteomics)
• Statistical modeling and machine learning for translational science
• Cross-functional collaboration and scientific communication