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# Principal Scientist Data Science

- **Company:** Johnson U0026 Johnson
- **Location:** Barcelona, Spain
- **Contract:** Permanent contract
- **Skills:** Continuous Integration, Information Extraction, Python (Programming Language), Operational Data Store, SQL Databases, Large Language Models, Gitlab, Git, Scikit Learn, Xgboost, Machine Learning Operations, Jenkins
- **Published:** August 11, 2026
- **Apply:** https://www.buscojobs.com.es/principal-scientist-data-science-en-barcelona-ID-366666591

## About the Role

Compensaciones / Beneficios * Conceive, develop, and implement ML, multi-objective optimization, and GenAI solutions for clinical trial operations * Build predictive models using operational, real-world data, and cost data to forecast outcomes and optimize scenarios * Adapt LLMs for information extraction and tasks like trial protocol comparison, data harmonization, activity scheduling, and eligibility evaluation * Run stochastic enrollment simulations to forecast enrollment and study completion * clearly articulate technical methods/results to diverse audiences to drive decisions * coach and train junior colleagues in techniques, processes, and responsibilities Responsabilidades * Ph.D. in a quantitative discipline or equivalent * 5+ years of industry experience in data science projects using ML, optimization, NLP, and GenAI * Hands-on experience with multi-modal ML and stochastic time-series forecasting * Experience building multi-objective optimization engines using
evolutionary algorithms, RL, or MILP * Experience with GenAI and clinical LLMs for document parsing and harmonization * Proficiency in MLOps (MLflow, Kedro); Git, CI/CD (Jenkins, GitLab) * Python and SQL programming; experience with Python LLM tools (DSPy, LangChain) and optimization/ML tools (pymoo, Scikit-learn, XGBoost, Optuna, PyMc) * Experience with clinical operational data, RWD, EHRs, claims, and financial data Requisitos principales *

## Description

Experteer Overview As Principal Scientist in Ju****amp;J Innovative Medicine, you will advance ML, optimization, and GenAI to streamline global clinical operations.You'll build predictive models and optimization engines to forecast enrollment, costs, and site selection, enabling proactive risk management.Collaborating across teams, you'll translate complex methods into actionable insights for decision-makers.This role offers impact at scale in a mission-driven, data-first environment.Compensaciones / Beneficios * Conceive, develop, and implement ML, multi-objective optimization, and GenAI solutions for clinical trial operations * Build predictive models using operational, real-world data, and cost data to forecast outcomes and optimize scenarios * Adapt LLMs for information extraction and tasks like trial protocol comparison, data harmonization, activity scheduling, and eligibility evaluation * Run stochastic enrollment simulations to forecast enrollment and study completion * clearly articulate technical methods/results to diverse audiences to drive decisions * coach and train junior colleagues in techniques, processes, and responsibilities Responsabilidades * Ph.D. in a quantitative discipline or equivalent * 5+ years of industry experience in data science projects using ML, optimization, NLP, and GenAI * Hands-on experience with multi-modal ML and stochastic time-series forecasting * Experience building multi-objective optimization engines using evolutionary algorithms, RL, or MILP * Experience with GenAI and clinical LLMs for document parsing and harmonization * Proficiency in MLOps (MLflow, Kedro); Git, CI/CD (Jenkins, GitLab) * Python and SQL programming; experience with Python LLM tools (DSPy, LangChain) and optimization/ML tools (pymoo, Scikit-learn, XGBoost, Optuna, PyMc) * Experience with clinical operational data, RWD, EHRs, claims, and financial data Requisitos principales *


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