Vice President - Data Science

## Vice President - Data Science Apply locations:
Tempe, AZ - 85281time type:
Full time posted on:
Posted Yesterday job requisition :
JR104839
** At Caris, we understand that cancer is an ugly word—a word no one wants to hear, but one that connects us all. That’s why we’re not just transforming cancer care—we’re changing lives.
** We introduced precision medicine to the world and built an industry around the idea that every patient deserves answers as unique as their DNA. Backed by cutting-edge molecular science and AI, we ask ourselves every day: *“What would I do if this patient were my mom?”
* That question drives everything we do. But our mission doesn’t stop with cancer. We're pushing the frontiers of medicine and leading a revolution in healthcare—driven by innovation, compassion, and purpose.
** Join us in our mission to improve the human condition across multiple diseases. If you're passionate about meaningful work and want to be part of something bigger than yourself, Caris is where your impact begins.
**** Position Summary
** 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, Num Py, 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…