Vice President - Data Science

The Vice President, Data Science provides senior leadership for Caris' AI-driven clinical insights and predictive modeling initiatives. This role leads the development of novel AI signatures leveraging Caris' large-scale clinico-genomic database to identify molecular characteristics of disease that are prognostic of patient outcomes or predictive of response to therapy.

The Vice President oversees a multidisciplinary team of data scientists, computational biologists, and translational researchers responsible for identifying clinically meaningful questions, developing and validating AI-based molecular signatures, and translating discoveries into scalable clinical reporting capabilities. Partnering with Executive Leadership, R&D, Clinical Development, Medical Affairs, Bioinformatics, Regulatory Affairs, and Commercial teams, this role ensures delivery of scientifically rigorous, clinically meaningful, and operationally scalable AI innovations that advance precision medicine.

Job Responsibilities

• Define and execute the strategy for AI-driven clinical insight and molecular signature development across Caris' molecular profiling platforms.
• Identify clinically relevant questions where advanced analytics can deliver prognostic or predictive insights.
• Oversee development of AI signatures 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 to ensure appropriate validation and evidence generation.
• Lead implementation of AI products within a regulated CAP/CLIA clinical environment.
• Oversee engineering and production deployment of AI pipelines within Caris' clinical reporting infrastructure.
• Ensure scalable, reproducible, auditable computational pipelines and canonical data models.
• Lead development of clinically interpretable reporting frameworks for physicians.
• Partner with Product and Commercial teams to integrate AI insights into clinical reports and decision-support tools.
• Build, mentor, and lead high-performing teams of data scientists and computational biologists.
• Set organizational goals, budgets, roadmaps, OKRs, and performance metrics aligned with corporate priorities.
• Champion a culture of scientific rigor, accountability, transparency, and continuous improvement.

Required Qualifications

• PhD in Data Science, Biostatistics, Computer Science, Biomedical Engineering, or a related field.
• 10+ years of experience building and implementing supervised and unsupervised machine learning models for complex problem solving.
• Expert proficiency in Python (pandas, NumPy, statistical and ML libraries) and SQL.
• Strong expertise in machine learning, statistical modeling, and large-scale biomedical data analysis.
• Experience working with multi-omic datasets including genomics, transcriptomics, and proteomics.
• Experience leveraging large clinical datasets for biomarker discovery, predictive modeling, or outcomes research.
• Working knowledge of regulatory considerations for algorithm development in clinical diagnostics environments.
• Demonstrated people leadership and direct management experience with accountability for large-scale outcomes.
• Outstanding verbal and written communication skills.
• This is an onsite role based at our Phoenix, AZ office and requires regular in-person presence.

Preferred Qualifications

• Experience working in regulated clinical laboratory environments (CAP/CLIA).
• Familiarity with cloud computing platforms and large-scale data infrastructures.
• Experience translating advanced analytics into physician-facing clinical products.