VP, Bioinformatics & Computational Oncology

About the Company

Our client is a rapidly developing clinical-stage biotechnology company focused on highly personalized cancer therapeutics, with a particular emphasis on individualized mRNA-based cancer vaccines.

The company is building a technology platform designed to translate patient-specific tumor biology into personalized therapeutic products. As the organization advances its clinical programs and increases patient volume, it is seeking a senior computational leader to own and scale the bioinformatics infrastructure underpinning this process.

This is a highly visible opportunity to join an ambitious, technically sophisticated organization at a pivotal stage of development.

The Opportunity

The company is seeking a Director / VP, Bioinformatics & Computational Oncology to take ownership of its computational and bioinformatics infrastructure supporting personalized cancer vaccine programs.

This is not a pure management position . The successful individual will initially remain highly hands-on, working directly with patient sequencing data, developing and improving production pipelines, investigating complex genomic findings, and collaborating closely with scientific and clinical teams.

The role will span the complete computational workflow from patient tumor sequencing through genomic interpretation, neoantigen identification and prioritization, and personalized vaccine design .

Over time, the individual will establish the architecture, processes and team required to transform an increasingly patient-specific workflow into a scalable computational platform capable of supporting significantly greater clinical volume.

Key Responsibilities

Computational Oncology & Patient-Specific Genomics

• Own the computational analysis supporting individualized cancer vaccine programs from raw patient sequencing data through vaccine design.
• Lead production analysis of tumor/normal WES and WGS and tumor RNA-seq datasets.
• Develop and oversee workflows for:
• Somatic SNV and indel calling
• Copy-number and other genomic alterations
• Gene-expression analysis
• HLA typing
• Neoantigen identification and prioritization
• Structural-variant and fusion detection
• Integration of genomic and transcriptomic data
• Interpret patient-specific genomic and transcriptomic findings in the context of tumor biology, clonality, variant allele frequency and sequencing limitations.
• Independently investigate ambiguous or technically challenging patient-specific findings and determine the appropriate computational approach.
• Support scientific teams through patient design review and design-lock activities , translating complex computational findings into clear, actionable conclusions.

Production Bioinformatics Platform

• Take ownership of existing computational workflows and establish robust, reproducible production infrastructure.
• Build and maintain scalable bioinformatics pipelines capable of supporting multiple individual patient programs.
• Establish appropriate standards for:
• Quality control
• Data provenance
• Version control
• Reproducibility
• Pipeline validation
• Documentation
• Auditability
• Identify opportunities to automate manual elements of the current tissue-to-dose computational workflow.
• Develop infrastructure that allows increasing patient volume without a proportional increase in manual computational effort.
• Work across Linux/HPC and cloud-based computational environments as appropriate.

Technology & Innovation

• Evaluate and appropriately incorporate emerging computational approaches, including AI/ML and advanced models for biological data.
• Work with external AI and computational collaborators to translate promising approaches into practical, validated workflows.
• Evaluate opportunities to incorporate agentic workflows and automation into the broader computational platform.
• Balance scientific innovation with the robustness, reproducibility and traceability required for clinical-stage development.

Cross-Functional Collaboration

• Partner closely with scientists, immunologists, clinical teams and other technical functions throughout individual patient programs.
• Translate complex genomic and computational outputs into clear conclusions for non-computational stakeholders.
• Participate in patient-specific design discussions and contribute computational expertise to key development decisions.
• Work with external sequencing providers, technology partners and other collaborators where required.
• Ensure computational outputs are appropriately documented and communicated to support scientific, clinical and regulatory activities.

Team & Function Building

• Establish the long-term architecture and operating model for the company's computational biology and bioinformatics function.
• Initially remain an individual technical contributor while progressively building and leading a high-performing computational team.
• Recruit, mentor and develop bioinformatics and computational biology talent as the company's programs and patient volume expand.
• Define technical standards, development practices and scientific priorities for the function.
• Ultimately build a scalable organization capable of supporting multiple personalized therapeutic programs.

Required Experience

The ideal candidate will combine deep cancer genomics expertise with strong software and computational engineering capability .

Essential experience includes:

• Significant industry experience in bioinformatics, computational biology, computational oncology, cancer genomics or a closely related discipline .
• Deep experience working with NGS data , particularly:
• WES
• WGS
• Tumor RNA-seq
• Strong understanding and practical experience with somatic variant calling and interpretation .
• Strong understanding of tumor biology, including clonality, variant allele frequency, tumor purity and sequencing limitations.
• Demonstrated ability to develop and maintain production-grade bioinformatics pipelines , rather than simply operating commercial or pre-existing tools.
• Strong programming capability in Python and/or R .
• Strong experience working in Linux/HPC and/or cloud environments .
• Experience building reproducible computational workflows with appropriate QC, provenance, versioning and validation.
• Ability to independently investigate complex or ambiguous patient-specific genomic findings.
• Experience collaborating directly with biologists, clinicians and other scientific stakeholders.
• Demonstrated ability to operate in an entrepreneurial or rapidly changing environment where the individual is expected to build systems while simultaneously using them to support active programs .
• A willingness and ability to remain technically hands-on despite operating at Director, Senior Director or VP level.

Preferred Experience

Experience in one or more of the following would be highly advantageous:

• Personalized cancer vaccines
• mRNA-based cancer therapeutics
• Neoantigen discovery and prioritization
• HLA typing and antigen-presentation prediction
• RNA-based fusion and structural-variant analysis
• Immunopeptidomics
• TCR sequencing / immune repertoire analysis
• Clinical or regulated genomics
• CLIA/CAP laboratory environments
• Sequencing vendors or clinical sequencing workflows
• CDMO or clinical-development environments
• Cloud-based computational infrastructure
• AI/ML applied to genomics, oncology or biological datasets
• Experience translating computational research workflows into production systems
• Previous leadership of a computational biology or bioinformatics team

A PhD in Bioinformatics, Computational Biology, Genomics, Cancer Biology, Computer Science or a related discipline is preferred, although exceptional candidates with equivalent industry experience will be considered.

The Ideal Candidate

The strongest candidates are likely to be individuals who sit at the intersection of cancer biology, computational genomics and software engineering .

They should be scientifically sophisticated enough to understand why a particular patient-specific genomic finding matters, while being technically capable of building the pipeline required to identify and interpret that finding.

The company is not seeking:

• A pure people manager who has moved away from technical work.
• A generic data-science leader without deep cancer genomics experience.
• A software engineer without substantial biological and NGS expertise.
• A computational biologist whose experience is primarily academic or exploratory rather than production-oriented.

The ideal individual is a builder who can personally solve difficult computational problems today while establishing the architecture and team that will allow the organization to scale tomorrow.

Expected Progression

First 3–6 Months

• Take ownership of existing computational workflows.
• Become deeply familiar with active patient programs.
• Independently support patient-specific genomic analyses.
• Identify critical gaps in existing pipelines and infrastructure.
• Begin standardizing analysis, QC and documentation.

6–12 Months

• Establish reproducible and scalable workflows across patient programs.
• Improve automation and reduce manual computational effort.
• Integrate structural-variant and fusion analysis into the broader workflow.
• Strengthen provenance, validation and auditability.
• Support increasing patient volume without proportional increases in manual analysis.

Long Term

• Develop a scalable computational platform supporting the company's personalized therapeutic programs.
• Establish and lead the broader computational biology/bioinformatics function.
• Build and develop a high-performing technical team.
• Introduce appropriate AI/ML and automation capabilities.
• Establish computational infrastructure capable of supporting the company's continued clinical development and growth.

Seniority

The company is open to Director, Senior Director or VP-level candidates .

The title will be calibrated according to the individual's technical depth, leadership experience and ability to architect and build the broader function.

Regardless of title, the successful candidate will initially be expected to remain highly hands-on .

Compensation & Package

A competitive U.S. executive-level compensation package will be offered, including:

• Competitive base salary commensurate with experience and level
• Performance-based bonus
• Equity participation
• Comprehensive benefits package

The company is willing to calibrate compensation for an exceptional candidate with highly relevant personalized oncology, cancer genomics, mRNA vaccine or neoantigen experience.

Why This Opportunity

This is an opportunity to take ownership of a critical computational function at a company developing highly personalized cancer therapeutics.

The successful candidate will have the opportunity to:

• Own the computational architecture underlying personalized therapeutic design.
• Work directly with real patient genomic data and active clinical programs.
• Solve technically challenging problems at the intersection of cancer biology, genomics and computational science.
• Build production infrastructure rather than simply maintain established systems.
• Influence the company's technology strategy as the platform scales.
• Build and eventually lead the computational biology organization.
• Work at the intersection of precision oncology, personalized vaccines, NGS, computational biology and AI .