Senior Data Scientist - Biologics Discovery & ML Data

jj; Madrid; Presencial; EUR 55.000 - 88.000; Jornada completa

Descripción de la vacante

Johnson & Johnson Innovative Medicine in Madrid, Spain, seeks a Senior Data Scientist focused on biologics discovery. You will design robust featurization and curate model-ready datasets, collaborating with ISD and discovery scientists to drive ML-enabled decisions.

Join a team building molecular design and predictive models, shaping AI applications across DMTL, and advancing analytics in a global biopharma context.

Formación

• Master's or PhD in CS, ML, computational biology, bioinformatics, statistics or related field.
• At least 2 years of applied ML experience with model development and dataset curation.
• Strong Python and ML stack proficiency (PyTorch, scikit-learn) and SQL.
• Experience turning heterogeneous data into robust features for training.
• Ability to collaborate with experimental scientists in a matrixed R&D environment.

Responsabilidades

• Apply data science to integrate and characterize diverse biologics data.
• Translate questions into data and analytical requirements for DMTL.
• Identify data quality issues and risks affecting modeling.
• Develop model-ready datasets and featurization for ISD models.
• Collaborate with ISD and discovery scientists to ensure reproducibility and responsible AI.

Conocimientos

Advanced Analytics

Business Intelligence

Coaching

Collaboration

Critical Thinking

Data Analysis

Database Management

Data Privacy Standards

Data Reporting

Data Savvy

Data Science

Data Visualization

Econometric Models

Process Improvements

Technical Credibility

Technologically Savvy

Workflow Analysis

Educación

Master's or PhD in CS/ML/Computational Biology/Bioinformatics/Statistics

Herramientas

PyTorch

Scikit-learn

SQL

Descripción del empleo

Johnson & Johnson Innovative Medicine in Madrid, Spain, seeks a Senior Data Scientist focused on biologics discovery. You will design robust featurization and curate model-ready datasets, collaborating with ISD and discovery scientists to drive ML-enabled decisions.

Join a team building molecular design and predictive models, shaping AI applications across DMTL, and advancing analytics in a global biopharma context.