**facilitar la aplicación a ofertas de trabajo con LinkedIn**. Si deseas obtener informaciónmás detallada,consultanuestra BBVA es una compañía global con más de 160 años de historia que opera en más de 25 países donde damos servicio a más de 80 millones de clientes. Somos más de 121.000 profesionales trabajando en equipos multidisciplinares con perfiles tan diversos como financieros, expertos legales, científicos de datos, desarrolladores, ingenieros y diseñadores.**Conoce más sobre el área:**BBVA AI Factory operates as a global hub within the Data area of BBVA, with development centers in Spain, Mexico, and Turkey.Our mission is to build complete, end-to-end data products that solve BBVA's business needs by working closely with business units to transform strategic priorities into actionable, data-driven solutions. Some of our recent projects include:* Mercury Library, an in-house AI framework now available to the entire data community, aimed at boosting collaboration and accelerating AI solution development.* A machine learning pipeline designed to enhance early debt recovery by predicting default risk and optimizing collection strategies* Applying daily life embeddings to drive deeper personalization in customer interactions and improve service recommendations.* Utilizing conformal prediction to provide reliable uncertainty estimates and enhance the confidence in AI model predictions* Building algorithmic explainability frameworks to ensure transparency and foster trust in our AI systems.At BBVA AI Factory, innovation isn’t just a goal-it’s a continuous journey.****Why You'll Love Working Here******Sobre el puesto*****\*Vacante publicada hasta el 17 de diciembre del 2025.*******Key job responsibilities:********Strategic & Analytical Leadership***** Act as the analytical reference for the Collections program, ensuring all data initiatives align with the broader Risk strategy and business priorities.* Define and maintain a clear roadmap and planning for all analytical lines of work, ensuring feasibility, sequencing, and delivery commitments.****Stakeholder & Product Collaboration***** Work closely with Product Owners and key stakeholders across Risk, Collections, Engineering, and Architecture.* Understand the functionality and business logic behind each line of work to design technically sound and business-aligned solutions.* Communicate progress, insights, risks, and recommendations clearly to both technical and non-technical audiences.### ****Technical Excellence & Solution Design***** Design and lead the end-to-end execution of advanced ML solutions, including model definition, experimentation strategy, architecture of the pipeline, and production deployment.* Create high-level and detailed solution designs, making key decisions on algorithms, architecture, features, evaluation, and scalability.* Drive forward-looking analytical practices such as causal inference, conformal prediction, explainability, fairness, and uncertainty modeling.### ****Hands-on Development & Model Oversight***** Guide (and when needed, contribute hands-on to) the development of models using our analytical stack: XGBoost, CatBoost, causal inference frameworks, conformal prediction, traditional ML and statistical modeling, etc.* Oversee the lifecycle of ML products: feature engineering, validation, testing, deployment, monitoring, and continuous improvement.* Ensure models are production-ready, efficient, and compliant with regulatory and governance standards.### ****Team Coordination***** Coordinate and mentor Data Scientists, ML Engineers, and Data Engineers.* Enable high-performing, collaborative teams through guidance, feedback, and technical direction.## ****Required Qualifications****### ### ****Experience***** 6+ years of experience in Data Science, Machine Learning, or AI developing end-to-end ML solutions (minimum requirement).* Proven experience leading analytical initiatives and collaborating with cross-functional teams.* Experience in credit risk, collections, or financial services is a strong plus.### ****Technical Skills***** Strong proficiency in Python, SQL, ML frameworks (scikit-learn, PyTorch, TensorFlow), and distributed processing (PySpark).* Strong knowledge of ML operations: pipeline design, monitoring, drift detection, retraining, CI/CD for ML.* Experience working in cloud environments (AWS, GCP, Azure).* Familiarity with explainable ML, fairness, uncertainty and governance practices.### ****Soft Skills***** Excellent communication skills to interact with stakeholders, PO, and leadership.* Ability to translate business needs into analytical solutions.* Strong planning and organizational abilities; comfortable managing several lines of work simultaneously.* Adaptability and resilience in fast-paced, evolving environments.* Leadership presence and the ability to guide and mentor multidisciplinary teams.**Habilidades:**Empatía, Ética, Innovación, Orientación al cliente, Pensamiento proactivo* Be part of a team that helps create an easier, more personalized banking experience offering better service to our customers.* Work on incorporating state-of-the-art AI to improve key