Principal Scientist, Predictive Modeling – Applied AI

This is a fully remote position, open to applicants in New York.

📋 Description

• In this position, you will serve as a scientific leader within the Research Sciences (RS) organization, contributing to our Scientific Engagement and Applied Research (SEAR) function by innovating and transforming predictive modeling techniques—such as digital twins and other sophisticated simulation frameworks—into actionable solutions for pharmaceutical and academic collaborators.

• Oversee the design, development, and validation of cutting-edge predictive modeling solutions for digital twins and other patient-level simulation methodologies, applicable in clinical development and related scenarios (e.g., trial design, cohort selection, endpoint prediction, treatment effect estimation, etc.).

• Propel a methodological strategy for existing and future use cases of applied AI in Real-World Data/Real-World Evidence (RWD/RWE) through the effective utilization of machine learning, deep learning, causal inference, and multimodal modeling techniques.

• Ensure that prediction models maintain scientific rigor, clinical relevance, and alignment with decision-centric use cases.

• Act as the scientific lead during client interactions, collaborating closely with our Life Sciences Partnership team to implement or proactively create Flatiron’s modeling strategies and solutions tailored to biopharma clinical development requirements.

• Simplify intricate methodological concepts into clear, decision-oriented insights for both technical and non-technical audiences via presentations, reports, and other engagement methods.

• Function as the organization’s external scientific engagement representative for predictive modeling and applied AI, showcasing the company at national and international conferences, industry gatherings, and through publications and scientific communications.

• Lead the authorship of abstracts, manuscripts, and external publications, positioning Flatiron as a frontrunner in applied AI and predictive modeling.

• Create and distribute training on the use of predictive models and applied AI solutions to various cross-functional partners in a highly matrixed setting.

• Collaborate with Product, Engineering, and Data teams to develop reusable capabilities into existing or innovative scalable platforms for predictive analytics.

⛳️ Requirements

• You possess an advanced degree (MS, PhD, or equivalent experience) in a quantitative discipline (e.g., epidemiology, machine learning, biostatistics, data science, applied mathematics), or have demonstrated equivalent expertise through practical work in predictive modeling within industry contexts, including engagements with pharmaceutical or life sciences organizations, or academic/healthcare systems.

• You are proficient across a range of predictive modeling techniques, including 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.

• You have substantial experience in developing machine learning or predictive modeling solutions for clinical research or clinical care applications, such as digital twins and clinical trial simulations.

• You possess a strong understanding of clinical development operations and processes, including clinical development planning, clinical trial design, and analysis.

• You have extensive experience with Real-World Evidence (RWE) methods in oncology and are knowledgeable about the variables and endpoints commonly used in oncology RWE research, observational studies, and their relationship with randomized controlled trials.

• You are capable of navigating a matrixed, fast-paced environment while managing multiple high-priority projects.

• You are skilled in either Python or R programming.

• You have experience working with large-scale, longitudinal healthcare datasets (e.g., EHR, claims, or multimodal data).

🏝️ Benefits

• Enjoy work/life flexibility through adjustable working hours and flexible paid time off.

• Receive a comprehensive compensation package.

• Benefit from a 401(k) contribution to assist you in achieving your retirement planning objectives.

• Access financial health resources, including personalized financial advice.

• Utilize mental well-being tools and services.

• Take advantage of parental benefits and policies, including family-building care and generous leave.

• Explore path to parenthood programs supporting fertility, adoption, and surrogacy.

• Receive travel support for safe healthcare services.