Vice President - Data Science
Caris Life Sciences · Tempe, AZ · 1 wk ago
EngineeringFull-time
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.
- 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.
- Proficient in Microsoft Office Suite including Word, Excel, Outlook, and PowerPoint.
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.