Finance Data Science Engineer

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Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance

At Boston Scientific, we’ll give you the opportunity to harness all that’s 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, we’ll help you in advancing your skills and career. Here, you’ll 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.
We’re 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.

Finance Data Science Engineer

At Boston Scientific, you will find a collaborative culture driven by a passion for innovation that keeps us connected on the most essential level. With determination, imagination and a deep caring for human life, we’re solving some of the most important healthcare industry challenges. Together, we’re one global team committed to making a difference in people’s lives around the world. This is a place where you can find a career with meaningful purpose—improving lives through your life’s work.

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.

Responsibilities will be balanced depending on business needs, and will involve both hands‑on and strategic leadership:

• 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.
• 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.
• Identify, evaluate, and prototype Generative AI and Agentic AI use cases that create measurable business value.
• Translate research into practical, production‑ready applications.

• 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.

• 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.

• 5–10 years of experience in data science, applied machine learning, forecasting, or a related field.
• BSc/MSc…