Principal Data Scientist – AI/ML and Optimization

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: Barcelona, Spain, Cambridge, Massachusetts, United States of America, Madrid, Spain, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America Descripción del trabajo: J&J Innovative Medicine – Data, Data Science, and AI - Global Development (DDSAI GD) is recruiting a Principal Data Scientist – AI/ML and Optimization. The ideal candidate will leverage, adapt, and extend machine learning (ML), optimization techniques, and GenAI techniques to create computational pipelines supporting global clinical operations including enrollment forecasting, cost estimation and optimization, and country/site selection. The primary location is Madrid, Spain. Other listed locations will be considered if approved by the business. J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, neuroscience, and infectious disease. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about J&J Innovative Medicine, visit https://www.jnj.com/innovative-medicine Key responsibilities: - Conceive, develop, and implement ML, multi-objective optimization, GenAI solutions to support clinical trial operations. - Leverage operational, real-world (RWD), and cost data to develop ML models and optimization engines that support data-driven decision making across operational planning. Specifically: - Develop predictive ML models to forecast operational time-series outcomes and KPIs. - Formulate and solve optimization problems that quantify tradeoffs among competing objectives, such as cost, timelines, patient burden, quality, and operational efficiency. - Integrate predictive modeling with optimization techniques to evaluate alternative operational scenarios, assess potential outcomes, and recommend optimal strategies. - Build explainable decision-support systems that translate complex analytics into actionable insights, enabling proactive planning, early risk identification, and informed business decision making. - Adapt large language models (LLMs) for tailored information extraction and to create solutions including conducting comparative analytics on clinical trial protocols and trial similarity assessment, clinical trial data harmonization and standardization, schedule of activity optimization, and eligibility criteria evaluation - Stochastic enrollment simulations to forecast operational and patient journey outcomes including enrollment and study completion. - Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making. - Coaches and trains junior colleagues in techniques, processes, and responsibilities. Required qualifications: - A Ph.D. degree in a quantitative discipline (e.g., computer science, electrical and computer engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or similar), - 5+ years of industry experience delivering on data science projects using ML predictive modeling, multi-objective optimization, natural language processing, and GenAI. - Hands-on experience with multi-modal ML predictive modeling and stochastic simulations for time-series forecasting. - Experience building multi-objective optimization engines to navigate complex trade-offs using evolutionary algorithms, reinforcement learning, or mixed-integer linear programming. - Experience with GenAI and clinical LLMs for document parsing and clinical concept disambiguation and harmonization. - Proficient in MLOps practices and tools (MLflow, Kedro); Git usage, CI/CD stacks (Jenkins, GitLab) DevOps tools. - Proficiency with programming languages Python and SQL, - Experience with python LLM tools (e.g., DSPy, LangChain), optimization tools (e.g., pymoo) and ML tools (e.g., Scikit-learn, XGBoost, Optuna, PyMc), - Demonstrated experience and familiarity with clinical operational data, real world data, electronic health records and claims, and financial data. Preferred qualifications: - Prior experience in a data science AI/ML role in healthcare, MedTech, and pharmaceutical industries. - Hand-on experience utilizing clinical trial protocols, registry, cost data, CTMS, EDC and/or EHR to build ML models for estimating operational outcomes or RWE outcomes. #LI-GR #LI-Hybrid #JRDDS #JNJDataScience #JRD Habilidades requeridas: Habilidades deseables: Análisis avanzado, Análisis de datos, Análisis del flujo de trabajo, Calidad de los datos, Ciencia de datos, Credibilidad técnica, Estándares de privacidad de datos, Experto en datos, Fluidez digital, Mejoras de procesos, Modelos econométricos, Organización, Orientación, Pensamiento crítico, Pensamiento estratégico, Presentación de informes de datos, Visualización de datos El intervalo de salario base anual previsto para esta posición es: €61,800.00 - €106,260.00 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.