Senior Data Scientist & Digital Product Owner - AI Data

Boston Scientific; Indiana (PA); Hybrid; USD 130,000 - 180,000; Full time

Job summary

Boston Scientific in the United States seeks a Senior Data Scientist, Digital Product Owner to partner with the Global Quality team. You will define product vision, roadmaps and priorities, and deliver scalable data products on modern cloud platforms.

You will bridge business stakeholders and data engineering, transforming complex challenges into trusted analytics, AI-driven insights, and measurable value for quality, regulatory, and manufacturing domains.

Qualifications

• Bachelor's degree in data science, computer science, information systems, engineering, statistics, mathematics or a related discipline.
• 5+ years of experience in data science, analytics, data products, or related fields.
• Proven experience leading cross-functional initiatives.
• Experience with Agile delivery and product management.
• Experience in regulated environments such as medical devices or life sciences.

Responsibilities

• Partner with business leaders to identify high-value opportunities and define product requirements.
• Define and prioritize user stories, acceptance criteria, and milestones using Agile.
• Communicate roadmap progress, risks, dependencies, and outcomes to senior leadership.
• Establish KPIs and data governance principles for trusted enterprise data products.
• Collaborate with data engineering to design scalable, governance-driven data architectures.

Skills

Data science

Analytics

Data products

Digital transformation

Agile product management

Stakeholder engagement

Education

Bachelor's degree in data science, computer science, or related field

Master's degree (preferred)

Job description

Boston Scientific in the United States seeks a Senior Data Scientist, Digital Product Owner to partner with the Global Quality team. You will define product vision, roadmaps and priorities, and deliver scalable data products on modern cloud platforms.

You will bridge business stakeholders and data engineering, transforming complex challenges into trusted analytics, AI-driven insights, and measurable value for quality, regulatory, and manufacturing domains.