Senior AI/ML & Optimization Scientist

7300-Janssen-Cilag S.A. Legal Entity; Madrid; On-site; EUR 62,000 - 106,000; Full time

Benefits offered by this job

Annual bonus

Vacation days

Parental leave

Well-being reimbursement

Health insurance

Job summary

Johnson & Johnson is seeking a Principal Data Scientist – AI/ML and Optimization in Madrid, focusing on ML, optimization, and GenAI from a global perspective. You will design computational pipelines for enrollment forecasting, cost estimation, and country/site selection, collaborating across clinical operations and R&D teams.

The role emphasizes translating complex analytics into actionable insights, building scalable models, and mentoring junior staff while engaging with diverse stakeholders

Qualifications

• PhD in a quantitative discipline with 5+ years in data science.
• Experience delivering ML modeling, optimization, NLP, and GenAI.
• Proficient in MLOps, Python, SQL, and modern ML tooling.

Responsibilities

• Develop ML, optimization, and GenAI solutions for clinical ops.
• Create predictive models for time-series outcomes and KPIs.
• Build multi-objective optimization engines for trade-offs.
• Integrate modeling with optimization for scenario analysis.
• Develop explainable decision-support and enable proactive planning.
• Adapt LLMs for information extraction and analytics tasks.
• Communicate technical results to diverse stakeholders.
• Coach junior colleagues in methods and processes.

Skills

ML & GenAI

Optimization

Time-series Forecasting

NLP

Python

SQL

MLOps

Data Visualization

Education

PhD in quantitative discipline

Tools

MLflow

Kedro

Git

Jenkins

LangChain

DSPy

pymoo

Scikit-learn

XGBoost

Optuna

PyMC

Job description

Johnson & Johnson is seeking a Principal Data Scientist – AI/ML and Optimization in Madrid, focusing on ML, optimization, and GenAI from a global perspective. You will design computational pipelines for enrollment forecasting, cost estimation, and country/site selection, collaborating across clinical operations and R&D teams.

The role emphasizes translating complex analytics into actionable insights, building scalable models, and mentoring junior staff while engaging with diverse stakeholders