Experteer Overview

In this role you will lead advanced data science work to optimize global clinical operations at Ju0026amp;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 / Incentivos

- 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, Git Lab)
- Proficiency in Python and SQL; experience with python LLM tools (DSPy, Lang Chain) and optimization tools (pymoo)
- Experience with clinical operational data, RWD, EHR/claims, and financial data

Requisitos principales

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📌 Principal Scientist Data Science (Madrid)
🏢 Johnson u0026 Johnson
📍 Madrid