Principal Scientist (Predictive Modeling & Applied AI)

TL;DR

Principal Scientist, Predictive Modeling & Applied AI: Lead the design, development, and validation of advanced predictive modeling solutions like digital twins and patient-level simulations for clinical development with an accent on machine learning, deep learning, causal inference, and multimodal modeling. Focus on ensuring scientific rigor, clinical grounding, and alignment to decision-oriented use cases in oncology RWE, trial design, cohort selection, and treatment effect estimation.

Location: NY office or Remote - US

Company

hirify.global is reimagining the infrastructure of cancer care using real-world data to improve lives.

What you will do

• Lead design, development, and validation of predictive models for digital twins and clinical simulations in trial design, cohort selection, endpoint prediction, and treatment effects.
• Advance methodological strategies using ML, deep learning, causal inference, and multimodal approaches for RWD/RWE use cases.
• Serve as scientific lead in client engagements, translating models into decision-relevant insights for biopharma partners.
• Represent the company externally through conferences, publications, and lead authorship of abstracts and manuscripts.
• Develop and deliver training on predictive models and applied AI to cross-functional teams.
• Partner with Product, Engineering, and Data teams to build scalable platforms for predictive analytics.

Requirements

• Advanced degree (MS, PhD or equivalent) in quantitative field like epidemiology, ML, biostatistics, data science
• Expertise in predictive modeling: gradient boosting (XGBoost), deep learning (neural networks for multimodal data), statistical methods for longitudinal/time-to-event data
• Strong experience in ML/predictive solutions for clinical research/care, e.g., digital twins, trial simulations
• Familiarity with clinical development, trial design/analysis, oncology RWE methods, variables, and endpoints
• Proficient in Python or R; experience with large-scale longitudinal healthcare datasets (EHR, claims, multimodal)
• Comfortable in matrixed, fast-paced environment balancing multiple priorities

Nice to have

• Experience in predictive modeling for early development, commercial analytics, HEOR
• Track record informing drug development decisions (target selection, go/no-go, launch)
• Experience in clinical trial data management, analytics, governance

Culture & Benefits

• Flexible work hours and paid time off for work/life autonomy
• Comprehensive compensation and 401(k) contributions
• Financial health resources and 1:1 advice
• Mental well-being tools and services
• Parental benefits including family-building care, fertility, adoption, surrogacy support
• Travel support for healthcare services