Flatiron Health
cancer care
PrincipalScientist,PredictiveModelingandAppliedAI(ClinicalDevelopment)
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“Principal Scientist, Predictive Modeling and Applied AI (Clinical Development) at Flatiron Health. Skills: predictive modeling, applied AI, clinical development, machine learning, deep learning, causal inference, Python, R. Lead the design, development, and validation of advanced predictive modeling solutions, for digital twins and other patient-level simulation approaches, in clinical development and adjacent use cases. Advance a methodological strategy against existing and future use cases for”
What You'll Achieve.
improve and extend lives by learning from the experience of every person with cancer; decision grade solutions for pharmaceutical and academic partners; achieve validity, interpretability, and fit-for-purpose use in clinical development; establishing Flatiron as a leader in applied AI and predictive modeling
Industry & Context.
problem-solver; propose model designs and select methodological approaches that achieve validity, interpretability, and fit-for-purpose use in clinical development
What They're Looking For.
Must Have
advanced degree (MS, PhD, or equivalent experience) in a quantitative field (e.g., epidemiology, machine learning, biostatistics, data science, applied mathematics), demonstrated expertise through applied work in predictive modeling in industry settings, including work with pharmaceutical or life sciences organizations, or academic/ healthcare systems, demonstrated experience applying predictive modeling or AI methods to oncology clinical development, RWD/RWE, or other regulated healthcare decision-making contexts, fluent across a spectrum of predictive modeling approaches spanning gradient boosting (e.g., XGBoost), deep learning (e.g., neural networks for multimodal clinical data), and advanced statistical methods for longitudinal/ time-to-event data, experience in developing machine learning or predictive modeling solutions for clinical research or clinical care applications such as digital twins, clinical trial simulations, familiarity with clinical development operations and processes, including clinical development planning, clinical trial design and analysis, experience in RWE methods in oncology, familiar with variables and endpoints commonly used in oncology RWE research, observational studies and their intersection with randomized controlled trials, comfortable operating in a matrixed, fast-paced environment and balancing multiple high-priority initiatives, proficient in Python OR R programming, experience with large-scale, longitudinal healthcare datasets (e.g., EHR, claims, or multimodal data)
Nice to Have
experience applying predictive modeling to other drug development areas of practice including Early development, Commercial Analytics, and HEOR, track record of applying predictive modeling to inform key drug development decisions across the lifecycle (e.g., target selection, trial design, go/no-go decisions, launch readiness), experience in clinical trial data management, analytics, and governance
What You'll Do.
and validation of advanced predictive modeling solutions
for digital twins and other patient-level simulation approaches
in clinical development and adjacent use cases
Advance a methodological strategy against existing and future use cases for applied AI in RWD/RWE by appropriate application of machine-learning
and multimodal modeling approaches
Ensures that prediction models are scientifically rigorous
and aligned to decision-oriented use cases
Serve as a scientific lead in client engagements
working closely with our Life Sciences Partnership team to apply
or proactively develop
Flatiron’s modeling strategies and solutions to biopharma clinical development needs
Translate complex methodological concepts into clear
decision-relevant insights for technical and non-technical stakeholders
Act as the organization’s external scientific engagement lead for predictive modeling and applied AI
representing the company at national and international conferences
and through publications and scientific communications
Lead authorship of abstracts
and external publications
Develop and disseminate training on the application of predictive models and applied AI solutions to multiple cross-functional partners
and Data teams to shape reusable capabilities into existing or novel scalable platforms for predictive analytics
How You'll Work.
Team & Collaboration
scientific leader within the Research Sciences (RS) organization, supporting our Scientific Engagement and Applied Research (SEAR) function; Serve as a scientific lead in client engagements, working closely with our Life Sciences Partnership team; Translate complex methodological concepts into clear, decision-relevant insights for technical and non-technical stakeholders through presentations, reports and other modes of engagement; Develop and disseminate training on the application of predictive models and applied AI solutions to multiple cross-functional partners in a highly matrixed environment; Partner with Product, Engineering, and Data teams
Communication Scope
Translate complex methodological concepts into clear, decision-relevant insights for technical and non-technical stakeholders through presentations, reports and other modes of engagement; external scientific engagement lead; representing the company at national and international conferences, industry forums, and through publications and scientific communications; Lead authorship of abstracts, manuscripts, and external publications
Full Job Description
Reimagine the infrastructure of cancer care within a community that values integrity, inspires growth, and is uniquely positioned to create a more modern, connected oncology ecosystem. We’re looking for a Principal Scientist in Predictive Modeling & Applied AI (Clinical Development) to help us accomplish our mission to improve and extend lives by learning from the experience of every person with cancer. Are you ready to be the next changemaker in cancer care? What You'll Do In this role, you will operate as a scientific leader within the Research Sciences (RS) organization, supporting our Scientific Engagement and Applied Research (SEAR) function, innovating and translating predictive modeling approaches—such as digital twins and other advanced simulation frameworks into decision grade solutions for pharmaceutical and academic partners. In this role you will propose model designs and select methodological approaches that achieve validity, interpretability, and fit-for-purpose use in clinical development. Specifically, you will: Lead the design, development, and validation of advanced predictive modeling solutions, for digital twins and other patient-level simulation approaches, in clinical development and adjacent use cases (e.g., trial design, cohort selection, endpoint prediction, treatment effect estimation, etc.) Advance a methodological strategy against existing and future use cases for applied AI in RWD/RWE by appropriate application of machine-learning, deep learning, causal inference, and multimodal modeling approaches Ensures that prediction models are scientifically rigorous, clinically grounded, and aligned to decision-oriented use cases Serve as a scientific lead in client engagements, working closely with our Life Sciences Partnership team to apply, or proactively develop, Flatiron’s modeling strategies and solutions to biopharma clinical development needs Translate complex methodological concepts into clear, decision-relevant insights for technical and
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