Finance Data Science Engineer, Madrid

Finance Data Science Engineer Additional Locations : Spain-Madrid France-Voisins le Bretonneux France- le-de-France Germany-D sseldorf Italy-Milan United Kingdom-Hemel Hempstead Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance At Boston Scientific, well give you the opportunity to harness all thats within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, well help you in advancing your skills and career. Here, youll be supported in progressing - whatever your ambitions. Boston Scientific transforms lives through innovative medical solutions that improve the health of more than 30 million patients around the world each year. Were at the forefront of the medical device industry - leading, evolving it to address unmet and emerging needs in healthcare. Our culture powers our performance and we turn our shared vision into value with the contribution of our 36.000 colleagues around the world. About Us As a Senior Data Scientist, you will join Finance EMEA to help build the AI Data Science vision from the ground up. This is a unique moment to join the team : we are in the early stages of developing our AI capabilities and scaling them across the function. You will play a leading role in executing and shaping the roadmap, driving technical excellence, and delivering advanced analytics and forecasting solutions that unlock tangible business value. Your work will span from designing cutting-edge forecasting methodologies, to implementing scalable data science products in cloud environments, to experimenting with Generative AI and Agentic technologies. You will also help set best practices for model governance, data quality, and stakeholder engagement. Your Responsibilities Will Be Responsibilities will be balanced depending on business needs, and will involve both hands-on and strategic leadership : Technical Leadership Delivery Lead the design, development, and deployment of advanced forecasting models using state-of-the-art libraries (e.g., statsforecast, Darts, skforecast, sklearn). Oversee end-to-end machine learning projects and pipelines from experimentation to production, ensuring scalability, reliability, and adherence to MLOps standards. Conduct robust accuracy assessments and ongoing performance monitoring of forecasting methodologies. Build, refine, and maintain high-quality Python codebases aligned with best software engineering practices. Explore data sets to uncover insights, define hypotheses, and answer complex business questions. Data Quality, Architecture Governance Collaborate with data engineering teams to ensure strong data foundations, including data quality, metadata management, lineage, and effective governance. Drive improvements in data architecture to support long-term analytical scalability. AI Innovation Experimentation Identify, evaluate, and prototype Generative AI and Agentic AI use cases that create measurable business value. Translate research into practical, production-ready applications. Business Impact Stakeholder Management Interact with Finance stakeholders, translating analytical outputs into actionable recommendations. Communicate complex technical concepts to non-technical audiences with clarity and precision. Facilitate the adoption of data science solutions through documentation, training, and change management. Team Development Mentor junior data scientists and interns, fostering a culture of continuous learning and technical excellence. Contribute to defining the long-term AI Data Science roadmap and team best practices. What Are We Looking For In You 5-10 years of experience in data science, applied machine learning, forecasting, or a related field. BSc / MSc in data science, data engineering, computer science, mathematics, engineering, or an equivalent field. A PhD is a plus. Deep expertise in Python, statistical modeling, forecasting techniques, and modern data science libraries. Strong experience deploying machine learning solutions in cloud environments (AWS or Azure), ideally with MLOps tooling. Demonstrated ability to work with large data sets and data engineering tools. Proven track record delivering high-impact analytical solutions in a business environment. Strong communication skills with experience influencing senior stakeholders. Fluency in English required Spanish is a plus. Autonomy, creativity, and the ability to drive decisions and propose new ideas. Flexibility to adapt scope to evolving business needs. If you want to work in Madrid and you are looking for an internship in the Medical Device Industry, then apply for our Data Science internship today. Location : hybrid work mode schedule in our Madrid offices. Start date : February 2025 Python, MLOps #J-18808-Ljbffr