Senior Data Scientist (Biologics Discovery)

Location: Office-based in Spring House, PA; Titusville, NJ; Raritan, NJ; or Madrid, Spain. No remote option.

Base pay: €55,400–€87,860 annually, depending on pay grade and location.

Company

Johnson & Johnson develops healthcare, Innovative Medicine, and MedTech solutions focused on preventing and treating complex diseases.

What you will do

• Develop featurization approaches and model-ready datasets from antibody and protein sequences, constructs, assays, and biophysical data.
• Define features, labels, and aggregation levels with data engineers while preserving important raw representations.
• Curate, document, and version datasets to support reproducible and traceable modeling.
• Build and evaluate applied ML models and evaluation frameworks for biologics discovery data.
• Collaborate with In Silico Discovery, experimental scientists, ontology specialists, and MLOps colleagues across the design-make-test-learn cycle.
• Support responsible AI, consistent data semantics, and reliable movement of models from development into use.

Requirements

• Master’s or Ph.D. 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 involving complex scientific or biomedical data.
• Strong proficiency in Python, PyTorch or scikit-learn, and SQL.
• Experience transforming heterogeneous experimental data into robust features and training sets, with exposure to cloud training and data infrastructure.
• Understanding of evaluation, validation, data leakage, and distribution shift risks.
• Ability to collaborate with experimental scientists and modeling partners in a matrixed R&D environment.

Nice to have

• Experience with biologics, antibody or protein sequence models, or protein language models.
• Experience with active learning, Bayesian optimization, or sequence-based generative models for molecular design.
• Familiarity with biophysical data, assay data, and developability endpoints.
• Experience with MLOps, experiment tracking, and model monitoring.
• Knowledge of ontologies or knowledge graphs for data reuse and AI-ready datasets.

Culture & Benefits

• Inclusive work environment based on individual consideration, diversity, and dignity.
• Annual bonus with a target determined by pay grade and location.
• Vacation, parental leave of at least 12 weeks, bereavement, caregiver, and volunteer leave.
• Well-being reimbursement and financial, physical, and mental health programs.
• Recognition awards and access to insurance plans subject to applicable plan terms and location eligibility.