Senior Data Scientist, Biologics Discovery - Madrid, ES

En Johnson & Johnson creemos que la salud lo es todo. Nuestra fuerza en la innovación en la atención médica nos permite construir un mundo en el que se eviten, traten y curen enfermedades complejas, en el que los tratamientos sean más inteligentes y menos invasivos, y las soluciones sean personales. A través de nuestra experiencia en Medicina Innovadora y MedTech, estamos en una posición única para innovar en todo el espectro de soluciones de atención médica de hoy para ofrecer los avances del futuro y afectar profundamente a la salud para la humanidad. Obtenga más información en jnj.com Guiados por nuestro Credo, en Johnson & Johnson somos responsables de nuestros empleados que trabajan con nosotros en todo el mundo. Proporcionamos un entorno laboral inclusivo donde cada persona es tratada como individuo. En Johnson & Johnson, respetamos la diversidad y la dignidad de nuestros empleados y reconocemos sus méritos. Función de trabajo: Data Analytics & Computational Sciences Subfunción de trabajo: Data Science Categoría de trabajo: Scientific/Technology Todas las ubicaciones de colocación de trabajo: Madrid, Spain Descripción del trabajo: Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way. Learn more at https://www.jnj.com/innovative-medicine About the opportunity Johnson & Johnson Innovative Medicine is seeking a Senior Data Scientist dedicated to our Biologics Discovery organization. This role sits within our Data Science team and partners closely with our In Silico Discovery (ISD) organization - the group that builds the molecular design and property-prediction models (for example, developability, affinity and binding, and other molecular-property and liability-risk models) that guide which biologic molecules to design, make, and advance. ISD owns core molecular model development; you will build the data-facing ML capabilities (featurization, model-ready datasets) that make ISD's models faster to build and better to trust. This position will be based at one of our office locations in either Spring House, PA (strongly preferred), Titusville, NJ, or Raritan, NJ, USA; or Madrid, Spain. (No remote option.) Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s): USA - Requisition Number: R-095854 Spain - Requisition Number: R-096793 Why this role matters: Biologics Discovery is generating rich, fast-growing data across assays, sequences, and modalities, and the opportunity now is to make that data fully model-ready and seamlessly available for ML. This role ensures biologics data is structured for training, and that applied ML on discovery data helps scientists prioritize molecules, flag risks, and generate hypotheses earlier - strengthening the interface to ISD's models rather than duplicating them. Position Summary You will design robust featurization approaches and curate standardized, traceable, model-ready datasets from biologics assay, biophysical, sequence, and construct data. You operate at the interface between our data-generating and data-infrastructure partners and In Silico Discovery (ISD), ensuring the datasets and features you create strengthen ISD's molecular property models. This is an opportunity to shape how AI learns from every biologics experiment. Key Responsibilities Scientific Data Analysis & Enablement - Apply modern data science tools to explore, integrate, and characterize heterogeneous biologics discovery data (e.g., antibody/protein sequence, construct, assay, and biophysical data). - Work with discovery scientists to translate scientific questions and DMTL (design-make-test-learn) decision points into clear data and analytical requirements. - Identify data quality issues, biases, gaps, and risks such as leakage or distribution shift that could affect downstream modeling or scientific interpretation. - Support the effective use of data for molecule prioritization, risk identification, and hypothesis generation. Featurization & Model-Ready Data - Develop featurization and model-ready datasets from biologics discovery data. - Work with data engineers to specify the features, labels, and levels of aggregation that models need, preserving raw representations where information matters. - Curate, document, and version datasets so modeling is reproducible and traceable. Partnership, Rigor & Growth - Collaborate with ISD to hand off standardized, traceable training datasets and align on where Data Science enables versus where ISD owns modeling. - Partner with Discovery scientists to frame ML problems around real decision points in the design-make-test-learn (DMTL) cycle. - Work closely with ontology and MLOps colleagues so datasets carry consistent semantics and models move reliably from development into use. - Champion reproducibility, documentation, and responsible AI. Why This Role Is Unique This is an opportunity to apply ML where it truly moves the needle in biologics discovery - grounded in real assay and sequence data, tightly partnered with world-class molecular modeling, and with real room to grow your scope, technical leadership, and impact as you build a track record of delivery. Qualifications Required - 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. - 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 and training sets, 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. Preferred - Experience with biologics, antibody/protein sequence models, or protein language models. - Experience with active learning, Bayesian optimization, or sequence-based generative models for molecular design. - Familiarity with biophysical/assay data and developability endpoints. - Experience with MLOps, experiment tracking, and model monitoring. - Familiarity with how ontologies or knowledge graphs support data reuse and AI-ready datasets. This position will be based at one of our office locations in either Spring House, PA (strongly preferred), Titusville, NJ, or Raritan, NJ, USA; or Madrid, Spain. (No remote option.) #LI-SL #JNJDataScience #JNJIMRND-DS #JRDDS #LI-Hyrbid # 3 Habilidades requeridas: Habilidades deseables: Análisis avanzado, Análisis de datos, Análisis del flujo de trabajo, Ciencia de datos, Colaboración, Credibilidad técnica, Estándares de privacidad de datos, Experto en datos, Expertos en tecnología, Gestión de bases de datos, Inteligencia empresarial (BI), Mejoras de procesos, Modelos econométricos, Orientación, Pensamiento crítico, Presentación de informes de datos, Visualización de datos El intervalo de salario base anual previsto para esta posición es: €55,400.00 - €87,860.00 Beneficios: Además del salario base, ofrecemos los siguientes beneficios*: Una bonus variable anual con un objetivo o target preestablecido (% del salario fijo) en función del pay grade/ubicación, donde el importe a percibir se basa en el desempeño que hayan tenido durante el año natural anterior tanto los empleados como las empresas, o comisiones de ventas. Además, ofrecemos días de vacaciones, permiso parental por un mínimo de 12 semanas, permiso por duelo, permiso para cuidadores, permiso de voluntariado, reembolso de bienestar, programas de salud financiera, física y mental. Además, ofrecemos premios por aniversario de servicio y reconocimiento, y con sujeción a los términos de sus respectivos planes, los empleados, y los dependientes elegibles de algunas ubicaciones, pueden participar en varios planes de seguro. Para obtener más información, visite Employee benefits | Supporting well-being & career growth | Johnson & Johnson Careers. *Lo anterior se facilita con fines exclusivamente informativos. Los importes y los beneficios reales pueden variar según la ubicación y están sujetos a cambios.