• Apply statistical techniques (regression, distribution analysis, hypothesis testing) to derive insights from data and create advanced algorithms and statistical models such simulation, scenario analysis, and clustering • Explain complex models (e.g., RandomForest, XGBoost, Prophet, SARIMA) in an accessible way to stakeholders • Visualize and present data using tools such as Power BI, ggplot, and matplotlib • Explore internal datasets to extract meaningful business insights and communicate results effectively and write efficient, reusable code for data improvement, manipulation, and analysis • Manage project codebase using Git or equivalent version control systems • Design scalable dashboards and analytical tools for central use • Build strong collaborative relationships with stakeholders across departments to drive data-informed decision-making while also helping in the identification of opportunities for leveraging data to generate business insights • Enable quick prototype creation for analytical solutions and develop predictive models and machine learning algorithms to analyze large datasets and identify trends • Communicate analytical findings in clear, actionable terms for non-technical audiences • Mine and analyze data to improve forecasting accuracy, optimize marketing techniques, and informed business strategies, developing and managing tools and processes for monitoring model performance and data accuracy • Work cross-functionally to implement and evaluate model outcomes

• Lead end-to-end ML/AI solution architecture on AWS • Design and implement production-grade ML pipelines • Customize and deploy generative AI applications • Build scalable data processing and ETL pipelines • Develop MLOps practices • Optimize performance, cost, and scalability • Ensure security, compliance, and responsible AI • Collaborate with data engineers, data scientists, product teams, and stakeholders • Mentor junior engineers • Troubleshoot production issues

Role Description Dentro de nuestro área de Data internacional de Eraneos, buscamos un/a Data Scientist Mid-Level con sólida base técnica en análisis de datos, machine learning y estadística aplicada, capaz de desarrollar soluciones end-to-end y traducir resultados complejos en impacto de negocio. Formarás parte de un equipo multidisciplinar trabajando en casos reales, desde la exploración de datos hasta la puesta en producción de modelos, con especial foco en forecasting, NLP y modelos basados en transformers. Responsibilities - Analizar, limpiar y transformar grandes volúmenes de datos estructurados y no estructurados - Desarrollar modelos de machine learning y deep learning para problemas de negocio - Implementar soluciones de forecasting y series temporales - Diseñar y analizar experimentos (A/B testing) - Construir pipelines reproducibles de datos y modelos - Explicar resultados y modelos a stakeholders no técnicos - Colaborar con equipos de Data Engineering, BI y producto - Participar en el ciclo completo de modelos (MLOps) Qualifications - 2–5 años en roles de Data Science o similares - Capacidad para trabajar de forma autónoma en proyectos complejos - Enfoque práctico orientado a impacto en negocio Requirements - Python (avanzado) - PostgreSQL - SQL - Databricks - Pandas, NumPy - PySpark / Spark - Matplotlib, Seaborn o Plotly - Diseño de experimentos / A/B testing - Scikit-learn - Modelos de regresión y clasificación - Clustering (K-Means, DBSCAN…) - Feature engineering y selección de variables - Gradient boosting (XGBoost, LightGBM, CatBoost) - Validación de modelos y métricas (AUC, F1, RMSE…) - ARIMA / SARIMA - Prophet - Modelos con features temporales (LightGBM) - Fundamentos de redes neuronales - PyTorch o TensorFlow/Keras - CNNs y RNNs/LSTMs (nivel conceptual-práctico) - Preprocesamiento de texto (TF-IDF, embeddings) - Hugging Face Transformers - Modelos tipo BERT / RoBERTa - Fine-tuning de modelos - Prompt engineering y uso de APIs de LLMs - SHAP, LIME - Feature importance - MLflow - Git (GitHub/GitLab) - CI/CD (conceptual) - Código modular y testeable (Pytest/unittest) Benefits - Proyectos desafiantes con impacto real - Entorno moderno (cloud, MLOps, LLMs) - Equipo técnico de alto nivel - Crecimiento profesional continuo - Programa de certificaciones oficiales - Flexibilidad horaria y teletrabajo Company Description En Eraneos estamos comprometidos con el respeto a la diversidad y la igualdad de oportunidades. Estamos convencidos de que un equipo de trabajo diverso es la clave del éxito. Por ello, creamos un entorno laboral inclusivo, sin discriminar a ninguna persona por motivos de edad, orientación sexual, nacionalidad, religión, estado civil, discapacidad o identidad de género.

Role Description When our values align, there's no limit to what we can achieve. At Parexel, we all share the same goal - to improve the world's health. From clinical trials to regulatory, consulting, and market access, every clinical development solution we provide is underpinned by something special - a deep conviction in what we do. Each of us, no matter what we do at Parexel, contributes to the development of a therapy that ultimately will benefit a patient. We take our work personally, we do it with empathy and we're committed to making a difference. Key Accountabilities - Coordinate and lead a project team to successful completion of a project within timelines and budget. - Interact with clients as key contact with regard to statistical and contractual issues. - Perform QC of derived datasets, tables, figures and data listings produced by other members of the department. - Check own work in an ongoing way to ensure first time quality. - Understand and apply advanced statistical methods. - Lead production and quality control of randomizations, analysis plans, statistical reports, statistical sections of integrated clinical reports and other process supporting documents. - Provide a supporting role as a non-voting independent statistician providing data and analysis for DMC review. - Travel to, attend, and actively contribute to all kinds of client meetings as appropriate (e.g. discussing analysis concepts, presenting, discussing and interpreting study results). Business Development - Support of Business Development, e.g. by actively contributing to study design considerations in internal and client meetings. - Providing and discussing sample size scenarios. - Support of budget and proposal development. - Attending and preparing bid defense meetings for potential studies, programs of work and FSPs. General Activities - Additional responsibilities as defined by supervisor/manager. Qualifications - PhD in Statistics or related discipline with some experience or MS in Statistics or related discipline with significant experience. - The knowledge of pharmacokinetic data is an advantage. - Competent in written and oral English in addition to local language. Requirements - Good analytical skills. - Good project management skills. - Professional attitude. - Attention to detail. - Thorough understanding of statistical issues in clinical trials. - Prior experience with SAS programming required. - Ability to work independently. - Good leadership skills. - Good business awareness/business development. - Willingness to work in a matrix environment and to value the importance of teamwork. Education - PhD in Statistics or related discipline. - MS in Statistics or related discipline.