About the Role
The individual in this position will drive innovation in predictive analytics and AI applications by designing, building, and validating models that translate complex health data into actionable insights for clinical and operational use.
Responsibilities
- Lead the design and implementation of machine learning models to solve high-impact healthcare problems
- Translate clinical questions into data-driven modeling approaches
- Collaborate with cross-functional teams including engineers, clinicians, and product specialists
- Oversee model validation and performance evaluation across diverse datasets
- Ensure modeling practices align with regulatory and ethical standards
- Mentor data scientists and contribute to technical strategy
- Publish findings in peer-reviewed venues when appropriate
- Stay current with advancements in AI and predictive analytics
- Guide the integration of models into production systems
- Advocate for best practices in data quality and model interpretability
- Develop scalable pipelines for training and deploying models
- Work closely with clinical experts to refine problem definitions
- Communicate technical results to non-technical stakeholders
- Identify opportunities for automation and system optimization
- Support the development of internal tools for model monitoring
- Contribute to long-term research and development roadmaps
- Evaluate third-party AI tools and methodologies for potential adoption
- Ensure reproducibility and documentation of modeling workflows
- Participate in data governance initiatives
- Lead pilot studies for novel AI applications in oncology and beyond
Compensation
Competitive salary and benefits package commensurate with experience
Work Arrangement
Hybrid work model with flexibility based on team and role requirements
Team
Collaborative environment within a data science and engineering team focused on real-world health data
About the Role
This position sits at the intersection of data science, software engineering, and clinical research, aiming to transform raw health data into models that support better decision-making. The scientist will work on end-to-end development—from ideation to deployment—of AI systems that address real challenges in patient care and research.
What We Value
We prioritize scientific rigor, collaboration, and the ability to translate complex technical work into tangible healthcare impact. Candidates should demonstrate a balance of deep technical expertise and the ability to work effectively across disciplines.
Available for qualified candidates
