Vice President - Data Science
Caris Life Sciences
July 03, 2026
On-site
Tempe, AZ
IT
Position Summary
The Vice President, Data Science provides senior leadership for AI-driven clinical insights and predictive modeling initiatives, leading development of novel AI signatures to identify molecular characteristics of disease that are prognostic of patient outcomes or predictive of response to therapy.
Job Responsibilities
- Define and execute strategy for AI-driven clinical insight and molecular signature development across molecular profiling platforms.
- Identify clinically relevant questions for prognostic/predictive analytics.
- Oversee AI signature development integrating genomic, transcriptomic, proteomic, and clinical outcomes data.
- Establish governance and standards for model development, validation, documentation, and lifecycle management.
- Collaborate with Regulatory and Clinical Development teams for validation and evidence generation.
- Lead implementation of AI products in a regulated CAP/CLIA clinical environment.
- Oversee engineering and production deployment of AI pipelines within clinical reporting infrastructure.
- Ensure scalable, reproducible, auditable pipelines and canonical data models.
- Lead development of clinically interpretable physician reporting frameworks.
- Partner with Product and Commercial teams to integrate AI insights into clinical reports and decision-support tools.
- Build, mentor, and lead data science/computational biology teams.
- Set goals, budgets, roadmaps, OKRs, and performance metrics.
- Champion scientific rigor, accountability, transparency, and continuous improvement.
Required Qualifications
- PhD in Data Science, Biostatistics, Computer Science, Biomedical Engineering, or related field.
- 10+ years building/implementing supervised and unsupervised ML models.
- Expert in Python (pandas, NumPy, statistical/ML libraries) and SQL.
- Strong ML, statistical modeling, and large-scale biomedical data analysis.
- Experience with multi-omic datasets (genomics, transcriptomics, proteomics).
- Experience with large clinical datasets for biomarker discovery/predictive modeling/outcomes research.
- Working knowledge of regulatory considerations for clinical diagnostics algorithms.
- Demonstrated people leadership/management with accountability for large-scale outcomes.
- Outstanding verbal and written communication.
- Proficient with Microsoft Office (Word, Excel, Outlook, PowerPoint).
- Onsite role in Phoenix, AZ with regular in-person presence.
Preferred Qualifications
- Experience in regulated clinical laboratory environments (CAP/CLIA).
- Familiarity with cloud computing and large-scale data infrastructures.
- Experience translating analytics into physician-facing clinical products.
Physical Demands
- Ability to sit, stand, and work at a computer for extended periods.
Training
- Job-specific, safety, and compliance training as assigned.
Other
- May require occasional after-hours work and occasional travel.
The Vice President, Data Science provides senior leadership for AI-driven clinical insights and predictive modeling initiatives, leading development of novel AI signatures to identify molecular characteristics of disease that are prognostic of patient outcomes or predictive of response to therapy.
Job Responsibilities
- Define and execute strategy for AI-driven clinical insight and molecular signature development across molecular profiling platforms.
- Identify clinically relevant questions for prognostic/predictive analytics.
- Oversee AI signature development integrating genomic, transcriptomic, proteomic, and clinical outcomes data.
- Establish governance and standards for model development, validation, documentation, and lifecycle management.
- Collaborate with Regulatory and Clinical Development teams for validation and evidence generation.
- Lead implementation of AI products in a regulated CAP/CLIA clinical environment.
- Oversee engineering and production deployment of AI pipelines within clinical reporting infrastructure.
- Ensure scalable, reproducible, auditable pipelines and canonical data models.
- Lead development of clinically interpretable physician reporting frameworks.
- Partner with Product and Commercial teams to integrate AI insights into clinical reports and decision-support tools.
- Build, mentor, and lead data science/computational biology teams.
- Set goals, budgets, roadmaps, OKRs, and performance metrics.
- Champion scientific rigor, accountability, transparency, and continuous improvement.
Required Qualifications
- PhD in Data Science, Biostatistics, Computer Science, Biomedical Engineering, or related field.
- 10+ years building/implementing supervised and unsupervised ML models.
- Expert in Python (pandas, NumPy, statistical/ML libraries) and SQL.
- Strong ML, statistical modeling, and large-scale biomedical data analysis.
- Experience with multi-omic datasets (genomics, transcriptomics, proteomics).
- Experience with large clinical datasets for biomarker discovery/predictive modeling/outcomes research.
- Working knowledge of regulatory considerations for clinical diagnostics algorithms.
- Demonstrated people leadership/management with accountability for large-scale outcomes.
- Outstanding verbal and written communication.
- Proficient with Microsoft Office (Word, Excel, Outlook, PowerPoint).
- Onsite role in Phoenix, AZ with regular in-person presence.
Preferred Qualifications
- Experience in regulated clinical laboratory environments (CAP/CLIA).
- Familiarity with cloud computing and large-scale data infrastructures.
- Experience translating analytics into physician-facing clinical products.
Physical Demands
- Ability to sit, stand, and work at a computer for extended periods.
Training
- Job-specific, safety, and compliance training as assigned.
Other
- May require occasional after-hours work and occasional travel.