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Mid-Senior level
Posted March 28, 2026
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Responsibilities
Commitments
Responsibilities
- Design, implement, and validate machine learning models for early detection of ovarian cancer using multi-omics datasets
- Develop classifiers and predictive models integrating lipidomics, proteomics, metabolomics, and clinical data
- Optimize algorithms for robustness, reproducibility, and performance across diverse patient cohorts Biomarker & Assay Validation
- Lead validation of computational pipelines supporting biomarker combination strategies
- Perform rigorous statistical analysis to evaluate clinical performance
- Support analytical verification and validation efforts aligned with regulatory strategy Data Integration & Pipeline Development
- Develop scalable, reproducible computational workflows for multi-modal data integration
- Oversee data preprocessing, curation, normalization, and quality control
- Ensure computational infrastructure supports regulatory-compliant documentation Cross-Functional Collaboration
- Partner with wet lab scientists, biostatisticians, clinicians, regulatory advisors, and external collaborators
- Contribute to experimental design refinement and translational strategy
- Present complex data to both scientific and non-scientific audiences Leadership & Mentorship
- Provide technical and strategic direction to computational biology initiatives
- Mentor junior team members
Commitments
Contribute to a first-in-class diagnostic platform focused on early cancer detection in women
All full-time employees participate in a structured stock option program
Not Met Priorities
What still needs stronger evidence
Requirements
- Represent AOA Dx at scientific conferences and external engagements Qualifications
- 7+ years of experience in computational biology and multi-omics data analysis
- Expertise in machine learning, predictive modeling, and biomarker discovery, preferably in oncology diagnostics
- Strong programming skills in Python, R, or similar languages
- Experience working in high-performance computing environments
- Deep knowledge of cancer biology, signaling pathways, and statistical methods for multi-modal data analysis
- Demonstrated ability to independently architect and deploy production-level computational workflows
- Demonstrated experience leading computational projects in cross-functional environments
- Strong communication skills with ability to translate complex models into actionable insights Preferred Qualifications
- Experience with proteomics (immunoassay and/or LC-MS), lipidomics (LC-MS), and metabolomics platforms
- Experience supporting regulatory-compliant workflows and clinical assay development
- Strong publication record and/or patents in cancer diagnostics
- Prior leadership or mentoring experience in industry settings Why Join AOA Dx Impact & Ownership
Preferred Skills
- Strong communication skills with ability to translate complex models into actionable insights Preferred Qualifications
- Experience with proteomics (immunoassay and/or LC-MS), lipidomics (LC-MS), and metabolomics platforms
- Experience supporting regulatory-compliant workflows and clinical assay development
- Strong publication record and/or patents in cancer diagnostics
- Prior leadership or mentoring experience in industry settings Why Join AOA Dx Impact & Ownership
Education
- (Not required) – PhD in Computational Biology, Bioinformatics, Biostatistics, Computer Science, or related field (MS with significant experience considered)
Introduction AOA Dx exists to transform women’s health. We are leading the next generation of cancer diagnostics, applying lipidomics, proteomics, and machine learning to enable earlier diagnosis of ovarian cancer for women with signs and symptoms - an area where no diagnostic tool exists today. The Opportunity AOA Dx is seeking an experienced and innovative Associate Director-Principal Scientist, Computational Biology & Bioinformatics to lead development of machine learning models and computational pipelines supporting early detection of ovarian cancer. This role will serve as a scientific and technical leader within our multi-omics platform, integrating lipidomics, proteomics, metabolomics, and clinical data to build robust predictive models for diagnostic application. You will play a central role in transforming complex multi-modal datasets into clinically actionable biomarker configurations, supporting analytical validation and regulatory readiness. This is a high-impact leadership role for a computational scientist who combines deep cancer biology knowledge, advanced modeling expertise, and the ability to guide cross-functional teams toward milestone-driven execution. Key Responsibilities Algorithm & Model Development
Design, implement, and validate machine learning models for early detection of ovarian cancer using multi-omics datasets
Develop classifiers and predictive models integrating lipidomics, proteomics, metabolomics, and clinical data
Optimize algorithms for robustness, reproducibility, and performance across diverse patient cohorts Biomarker & Assay Validation
Lead validation of computational pipelines supporting biomarker combination strategies
Perform rigorous statistical analysis to evaluate clinical performance
Support analytical verification and validation efforts aligned with regulatory strategy Data Integration & Pipeline Development
Develop scalable, reproducible computational workflows for multi-modal data integration
Oversee data preprocessing, curation, normalization, and quality control
Ensure computational infrastructure supports regulatory-compliant documentation Cross-Functional Collaboration
Partner with wet lab scientists, biostatisticians, clinicians, regulatory advisors, and external collaborators
Contribute to experimental design refinement and translational strategy
Present complex data to both scientific and non-scientific audiences Leadership & Mentorship
Provide technical and strategic direction to computational biology initiatives
Mentor junior team members
Represent AOA Dx at scientific conferences and external engagements Qualifications
PhD in Computational Biology, Bioinformatics, Biostatistics, Computer Science, or related field (MS with significant experience considered)
7+ years of experience in computational biology and multi-omics data analysis
Expertise in machine learning, predictive modeling, and biomarker discovery, preferably in oncology diagnostics
Strong programming skills in Python, R, or similar languages
Experience working in high-performance computing environments
Deep knowledge of cancer biology, signaling pathways, and statistical methods for multi-modal data analysis
Demonstrated ability to independently architect and deploy production-level computational workflows
Demonstrated experience leading computational projects in cross-functional environments
Strong communication skills with ability to translate complex models into actionable insights Preferred Qualifications
Experience with proteomics (immunoassay and/or LC-MS), lipidomics (LC-MS), and metabolomics platforms
Experience supporting regulatory-compliant workflows and clinical assay development
Strong publication record and/or patents in cancer diagnostics
Prior leadership or mentoring experience in industry settings Why Join AOA Dx Impact & Ownership
Contribute to a first-in-class diagnostic platform focused on early cancer detection in women
Play a visible role in advancing a technology designed to change clinical outcomes Equity & Performance Alignment
All full-time employees participate in a structured stock option program
Equity aligned with company milestones and performance
Bonus pool and recognition programs designed to reward impact and culture embodiment
Employee referral program Compensation & Benefits
Competitive base salary
401(k) with employer match
Comprehensive medical, dental, and vision coverage
Employer-sponsored life and disability insurance
Unlimited PTO AOA Dx is an equal opportunity employer (EOE) and welcomes candidates from all backgrounds. We foster an environment where all people are afforded the freedom to pursue their passions without regard to race, color, religion, national or ethnic origin, gender (including pregnancy), sexual orientation or expression, age, disability or veteran status or any other characteristics protected by law.
Design, implement, and validate machine learning models for early detection of ovarian cancer using multi-omics datasets
Develop classifiers and predictive models integrating lipidomics, proteomics, metabolomics, and clinical data
Optimize algorithms for robustness, reproducibility, and performance across diverse patient cohorts Biomarker & Assay Validation
Lead validation of computational pipelines supporting biomarker combination strategies
Perform rigorous statistical analysis to evaluate clinical performance
Support analytical verification and validation efforts aligned with regulatory strategy Data Integration & Pipeline Development
Develop scalable, reproducible computational workflows for multi-modal data integration
Oversee data preprocessing, curation, normalization, and quality control
Ensure computational infrastructure supports regulatory-compliant documentation Cross-Functional Collaboration
Partner with wet lab scientists, biostatisticians, clinicians, regulatory advisors, and external collaborators
Contribute to experimental design refinement and translational strategy
Present complex data to both scientific and non-scientific audiences Leadership & Mentorship
Provide technical and strategic direction to computational biology initiatives
Mentor junior team members
Represent AOA Dx at scientific conferences and external engagements Qualifications
PhD in Computational Biology, Bioinformatics, Biostatistics, Computer Science, or related field (MS with significant experience considered)
7+ years of experience in computational biology and multi-omics data analysis
Expertise in machine learning, predictive modeling, and biomarker discovery, preferably in oncology diagnostics
Strong programming skills in Python, R, or similar languages
Experience working in high-performance computing environments
Deep knowledge of cancer biology, signaling pathways, and statistical methods for multi-modal data analysis
Demonstrated ability to independently architect and deploy production-level computational workflows
Demonstrated experience leading computational projects in cross-functional environments
Strong communication skills with ability to translate complex models into actionable insights Preferred Qualifications
Experience with proteomics (immunoassay and/or LC-MS), lipidomics (LC-MS), and metabolomics platforms
Experience supporting regulatory-compliant workflows and clinical assay development
Strong publication record and/or patents in cancer diagnostics
Prior leadership or mentoring experience in industry settings Why Join AOA Dx Impact & Ownership
Contribute to a first-in-class diagnostic platform focused on early cancer detection in women
Play a visible role in advancing a technology designed to change clinical outcomes Equity & Performance Alignment
All full-time employees participate in a structured stock option program
Equity aligned with company milestones and performance
Bonus pool and recognition programs designed to reward impact and culture embodiment
Employee referral program Compensation & Benefits
Competitive base salary
401(k) with employer match
Comprehensive medical, dental, and vision coverage
Employer-sponsored life and disability insurance
Unlimited PTO AOA Dx is an equal opportunity employer (EOE) and welcomes candidates from all backgrounds. We foster an environment where all people are afforded the freedom to pursue their passions without regard to race, color, religion, national or ethnic origin, gender (including pregnancy), sexual orientation or expression, age, disability or veteran status or any other characteristics protected by law.