Principal Scientist Data Science

Johnson & Johnson Innovative Medicine; Madrid; Presencial; EUR 102.000 - 175.000; Jornada completa

Descripción de la vacante

Johnson & Johnson Innovative Medicine is seeking a Principal Scientist to leverage ML, optimization, and GenAI to support global clinical operations, including enrollment forecasting and cost estimation. The role focuses on data from diverse sources and aims to enable proactive risk management and better decision-making.

The candidate will develop advanced computational pipelines, adapt LLMs for information extraction, and mentor junior colleagues while contributing to innovative healthcare

Formación

• Ph.D. in a quantitative field (e.g., CS, ECE, biostatistics, health economics, biomedical informatics, applied math).
• 5+ years delivering data science projects using ML, optimization, NLP, and GenAI.
• Hands-on multi-modal ML, stochastic simulations for time-series forecasting.
• Experience building multi-objective optimization engines (evolutionary algorithms, RL, MILP).
• GenAI and clinical LLMs for document parsing and harmonization.
• Proficient in MLOps and tools (MLflow, Kedro); Git/CI/CD stacks.
• Proficiency in Python and SQL; experience with Python LLM tools and ML libraries.
• Familiarity with clinical operational data, RWD, EHR, claims, and financial data.

Responsabilidades

• Conceive, develop, and implement ML, multi-objective optimization, and GenAI to support clinical operations.
• Build ML models and optimization engines using operational, RWD, and cost data.
• Adapt LLMs for tailored information extraction and analytics across protocols and trials.
• Run stochastic enrollment simulations to forecast outcomes and risks.
• Communicate technical methods and results clearly to diverse audiences.
• Coach and train junior colleagues in techniques and responsibilities.

Conocimientos

Advanced Analytics

Coaching

Critical Thinking

Data Analysis

Data Privacy Standards

Data Quality

Data Reporting

Data Savvy

Data Science

Data Visualization

Digital Fluency

Econometric Models

Organizing

Process Improvements

Strategic Thinking

Technical Credibility

Workflow Analysis

Python

SQL

Educación

Ph.D. in a quantitative discipline

Herramientas

MLflow

Kedro

Git

CI/CD (Jenkins, GitLab)

LangChain

DSPy

pymoo

Scikit-learn

XGBoost

Optuna

PyMC

Descripción del empleo

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function

Data Analytics & Computational Sciences

Job Sub Function

Data Science

Job Category

Scientific/Technology

All Job Posting Locations

Barcelona, Spain, Cambridge, Massachusetts, United States of America, Madrid, Spain, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description

J&J Innovative Medicine – Data, Data Science, and AI - Global Development (DDSAI GD) is recruiting a Principal Scientist. The ideal candidate will leverage, adapt, and extend machine learning (ML), optimization techniques, and GenAI techniques to create computational pipelines supporting global clinical operations including enrollment forecasting, cost estimation and optimization, and country/site selection.

J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, neuroscience, and infectious disease. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about J&J Innovative Medicine, visit https://www.jnj.com/innovative-medicine

Key Responsibilities

• Conceive, develop, and implement ML, multi-objective optimization, GenAI solutions to support clinical trial operations.
• Leverage operational, RWD, and cost data to build ML predictive models and optimization engines to 1) predict outcomes of interest, 2) highlight tradeoffs between competing objectives, 3) recommend optimal operational scenarios, and 4) generate actionable insights, enabling early intervention and risk management.
• Adapt large language models (LLMs) for tailored information extraction and to create solutions including
• conducting comparative analytics on clinical trial protocols and trial similarity assessment,
• clinical trial data harmonization and standardization,
• schedule of activity optimization, and
• eligibility criteria evaluation,
• Stochastic enrollment simulations to forecast operational and patient journey outcomes including enrollment and study completion.
• Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making.
• Coaches and trains junior colleagues in techniques, processes, and responsibilities.

Required Qualifications

• A Ph.D. degree in a quantitative discipline (e.g., computer science, electrical and computer engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or similar),
• 5+ years of industry experience delivering on data science projects using ML predictive modeling, multi-objective optimization, natural language processing, and GenAI.
• Hands-on experience with multi-modal ML predictive modeling and stochastic simulations for time-series forecasting.
• Experience building multi-objective optimization engines to navigate complex trade-offs using evolutionary algorithms, reinforcement learning, or mixed-integer linear programming.
• Experience with GenAI and clinical LLMs for document parsing and clinical concept disambiguation and harmonization.
• Proficient in MLOps practices and tools (MLflow, Kedro); Git usage, CI/CD stacks (Jenkins, GitLab) DevOps tools.
• Proficiency with programming languages Python and SQL,
• Experience with python LLM tools (e.g., DSPy, LangChain), optimization tools (e.g., pymoo) and ML tools (e.g., Scikit-learn, XGBoost, Optuna, PyMc),
• Demonstrated experience and familiarity with clinical operational data, real world data, electronic health records and claims, and financial data.

Preferred Qualifications

• Prior experience in a data science AI/ML role in healthcare, MedTech, and pharmaceutical industries.
• Hand-on experience utilizing clinical trial protocols, registry, cost data, CTMS, EDC and/or EHR to build ML models for estimating operational outcomes or RWE outcomes.

Required Skills

Advanced Analytics, Coaching, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Organizing, Process Improvements, Strategic Thinking, Technical Credibility, Workflow Analysis

Preferred Skills

Advanced Analytics, Coaching, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Organizing, Process Improvements, Strategic Thinking, Technical Credibility, Workflow Analysis

The anticipated base pay range for this position is :

$117,000.00 - $201,250.00