Senior Data Scientist, Biologics Discovery (Hybrid)

Johnson & Johnson Innovation; Madrid; Presencial; EUR 97.000 - 155.000; Jornada completa

Descripción de la vacante

Johnson & Johnson Innovative Medicine seeks a Senior Data Scientist to lead featurization and model-ready data creation for biologics discovery. You will build ML models on assay, biophysical, and sequence data and define evaluation frameworks that keep models trustworthy and ready for deployment.

You will collaborate with ISD and Discovery scientists to frame ML problems in the DMTL cycle, contributing to robust, reproducible data pipelines and responsible AI practices.

Formación

• Master's or PhD in Computer Science, Machine Learning, Computational Biology, Bioinformatics, Statistics, or a related field.
• At least 2 years of applied ML experience including model development, evaluation, and dataset curation on complex scientific or biomedical data.
• Strong proficiency with Python and the modern ML stack (e.g., PyTorch, scikit-learn) and SQL.
• Experience turning complex, heterogeneous experimental data into robust features with exposure to cloud training and data infrastructure.
• Sound understanding of evaluation, validation, and the risks of leakage and distribution shift.
• Ability to collaborate effectively with experimental scientists and modeling partners in a matrixed R&D environment.

Responsabilidades

• Featurization & Model-Ready Data: Develop featurization and model-ready datasets from antibody/protein sequence, construct, assay, and biophysical data.
• Applied ML & Evaluation: Build and evaluate models on bioscience data and define evaluation frameworks to keep models trustworthy.
• Partnership, Rigor & Growth: Collaborate with ISD to hand off standardized training datasets and align on where Data Science enables vs ISD owns modeling.

Conocimientos

Python

PyTorch

SQL

Machine Learning

Educación

MS/PhD CS/ML

Herramientas

scikit-learn

MLOps

Descripción del empleo

Johnson & Johnson Innovative Medicine seeks a Senior Data Scientist to lead featurization and model-ready data creation for biologics discovery. You will build ML models on assay, biophysical, and sequence data and define evaluation frameworks that keep models trustworthy and ready for deployment.

You will collaborate with ISD and Discovery scientists to frame ML problems in the DMTL cycle, contributing to robust, reproducible data pipelines and responsible AI practices.