Senior Data Scientist, Biologics Discovery
jj · Madrid
Descripcion del puesto
About the role
Johnson & Johnson Innovative Medicine is looking for a Senior Data Scientist for its Biologics Discovery organization, within the Data Science team. The role partners closely with In Silico Discovery (ISD), which builds molecular design and property-prediction models, and focuses on building the data-facing machine learning capabilities (featurization, model-ready datasets) that make those models faster and more trustworthy. The position is based in Madrid, Spain (no remote option); the same role is also posted for US offices.
Key responsibilities
- Analyze and integrate heterogeneous biologics discovery data (antibody/protein sequences, constructs, assays, biophysical data) and work with discovery scientists to turn scientific questions and DMTL decisions into data requirements.
- Identify data quality issues, biases, gaps and risks such as leakage or distribution shift.
- Develop featurization approaches and curate standardized, traceable, model-ready datasets from assay, biophysical, sequence and construct data.
- Work with data engineers to define features, labels and aggregation levels, and curate, document and version datasets so modeling is reproducible.
- Hand off datasets to ISD and partner with ontology and MLOps colleagues so models move reliably from development to use.
Required profile
- 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 on complex scientific or biomedical data.
- Ability to collaborate with experimental scientists and modeling partners in a matrixed R&D environment.
- Preferred: experience with biologics, antibody/protein sequence models or protein language models, active learning, Bayesian optimization, biophysical/assay data, MLOps and ontologies or knowledge graphs.
Required skills
- Strong Python and modern ML stack (PyTorch, scikit-learn) and SQL.
- Turning heterogeneous experimental data into robust features and training sets, with cloud training and data infrastructure exposure.
- Understanding of evaluation, validation and the risks of leakage and distribution shift.
What we offer
- Base pay range of EUR 55,400 to EUR 87,860.
- Annual bonus, vacation days, parental leave of at least 12 weeks, bereavement and caregiver leave, well-being reimbursement and health programs.
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Publicado hace 9 horas
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jj
Madrid