Principal Scientist Data Science

Experteer Overview In this role you will lead advanced data science work to optimize global clinical operations at Ju**amp;J Innovative Medicine.You will build ML and GenAI-enabled pipelines for enrollment forecasting, cost estimation, and site/country selection, partnering with cross-functional teams to drive decision-making.You will adapt LLMs for information extraction and harmonize clinical data to reveal actionable insights and risk management opportunities.This position offers a chance to shape digital capabilities that scale across clinical programs and contribute to better patient outcomes.Compensaciones / Beneficios * Conceive, develop, and implement ML, multi-objective optimization, GenAI solutions for clinical trial operations * Build ML predictive models and optimization engines using operational, real-world, and cost data to forecast outcomes and optimize scenarios * Adapt large language models for information extraction and diverse analytics such as protocol comparisons, data harmonization, and eligibility evaluation * Run stochastic enrollment simulations to forecast enrollment and study completion * Clearly articulate technical methods and results to diverse audiences to inform decisions * Coach and train junior colleagues in techniques and processes Responsabilidades * PhD in a quantitative discipline * 5+ years of industry experience in data science with ML, optimization, NLP, and GenAI * Hands-on experience with multi-modal ML and time-series forecasting * Experience building multi-objective optimization engines (evolutionary, RL, or MILP) * Experience with GenAI and clinical LLMs for document parsing and harmonization * Proficiency in ML Ops (MLflow, Kedro); Git; CI/CD (Jenkins, GitLab) * Proficiency in Python and SQL; experience with python LLM tools (DSPy, LangChain) and optimization tools (pymoo) * Experience with clinical operational data, RWD, EHR/claims, and financial data Requisitos principales *

Compensaciones / Beneficios * Conceive, develop, and implement ML, multi-objective optimization, GenAI solutions for clinical trial operations * Build ML predictive models and optimization engines using operational, real-world, and cost data to forecast outcomes and optimize scenarios * Adapt large language models for information extraction and diverse analytics such as protocol comparisons, data harmonization, and eligibility evaluation * Run stochastic enrollment simulations to forecast enrollment and study completion * Clearly articulate technical methods and results to diverse audiences to inform decisions * Coach and train junior colleagues in techniques and processes Responsabilidades * PhD in a quantitative discipline * 5+ years of industry experience in data science with ML, optimization, NLP, and GenAI * Hands-on experience with multi-modal ML and time-series forecasting * Experience building multi-objective optimization engines (evolutionary, RL, or MILP) * Experience with GenAI and clinical LLMs for document parsing and harmonization * Proficiency in ML Ops (MLflow, Kedro); Git; CI/CD (Jenkins, GitLab) * Proficiency in Python and SQL; experience with python LLM tools (DSPy, LangChain) and optimization tools (pymoo) * Experience with clinical operational data, RWD, EHR/claims, and financial data Requisitos principales *