Data and AI Capabilities Lead

Boston Scientific • Arden Hills, MN

4d • $106,800 - $202,900 • Hybrid

About The Position

The Data and AI Capabilities Lead helps Boston Scientific identify, shape, and advance high-value opportunities that use data, generative AI, agentic AI, and reusable AI capabilities to address business problems. The role connects business strategy, data, AI, product discovery, and technology delivery, partnering with divisions, regions, and functions to turn early ideas into investment-ready opportunities with clear value, feasibility, data readiness, adoption needs, and reusable capability fit.

The position focuses on the front end of the product lifecycle, including strategic relationship building, business problem discovery, workflow analysis, AI and data feasibility, solution shaping, and value realization planning. It works closely with Product Owners, AI Core Services, data teams, architecture, security, engineering, and business stakeholders so appropriate opportunities enter delivery and funded solutions are positioned to achieve business impact.

This position follows a hybrid work model and requires employees to work from a local office at least three days per week. Relocation assistance and employment visa sponsorship are not available for this position. The anticipated salary range is $106,800 to $202,900, with actual compensation depending on location, experience, training, education, and other relevant factors. Variable compensation may also be available, subject to plan eligibility and requirements.

Requirements

• Bachelor’s degree in Business, Engineering, Computer Science, Data Science, Information Systems, or a related field, or equivalent professional experience.
• At least five years of professional experience in digital product strategy, AI/data product management, business transformation, solution consulting, enterprise technology, experience architecture, or related roles; alternatively, at least eight years of such experience without a bachelor’s degree.
• Strong familiarity with large language models (LLMs), AI agents, prompt engineering, and enterprise use cases.
• Strong understanding of data and AI concepts, including generative AI, LLMs, agentic AI, analytics, data platforms, integrations, and enterprise data readiness.
• Technical fluency and curiosity, including the ability to discuss APIs, MCPs, integrations, data flows, application architecture, and system dependencies with engineers and architects.
• Interest in emerging AI technologies and their real-world applications, with the ability to quickly learn unfamiliar technologies, tools, and concepts.
• Demonstrated ability to work with business stakeholders to define problems, map workflows, identify value drivers, and shape technology-enabled solutions.
• Experience working with data, architecture, engineering, security, platform, and/or AI/ML teams to assess feasibility and solution options.
• Ability to determine whether required data exists, where it is located, how usable it is, and how data quality, governance, or access could affect feasibility.
• Strong facilitation, communication, and executive presence, and the ability to influence without direct authority.
• Ability to challenge assumptions and push back constructively while maintaining stakeholder trust.
• Strong analytical and strategic thinking skills, including the ability to connect business needs, data assets, AI capabilities, technical constraints, and adoption requirements.
• Comfort working in ambiguity and structuring early-stage ideas.
• Flexibility to collaborate across global time zones as business needs require.

Nice To Haves

• Experience shaping or delivering AI, generative AI, agentic AI, data, analytics, or automation solutions in an enterprise environment.
• Experience in healthcare, medtech, life sciences, regulated industries, or complex global organizations.
• Experience with product discovery, design thinking, business process redesign, value case development, or digital transformation.
• Familiarity with reusable platform capabilities, shared services, or enterprise capability roadmaps.
• Experience supporting annual planning, portfolio prioritization, investment shaping, or business case development.
• Ability to translate technical concepts into clear business language for non-technical stakeholders.
• Strong product mindset focused on outcomes, adoption, iteration, and measurable value.

Responsibilities

• Build trusted relationships with business sponsors, AI councils, functional leaders, data owners, and digital partners across divisions, regions, and functions.
• Advise stakeholders on AI capabilities, data readiness, and situations where AI may not be the appropriate solution.
• Identify similar needs across business areas and combine, redirect, or scale opportunities to avoid duplicative solutions.
• Facilitate workshops, interviews, and working sessions to understand workflows, pain points, decision points, data needs, users, operational constraints, and desired outcomes.
• Evaluate opportunities based on value, feasibility, repeatability, scale, data readiness, adoption readiness, and strategic alignment.
• Assess required data, where it resides, whether it is landed, governed, accessible, and usable, and how data gaps or quality issues may affect feasibility or value.
• Partner with data, architecture, AI engineering, AI Core Services, and AI platform teams to understand technical constraints, data dependencies, reusable services, and solution pathways.
• Shape end-to-end solution concepts that may combine multiple capabilities into cohesive workflow solutions.
• Identify recurring demand patterns to inform the AI Core Services and AI Farm capability roadmap.
• Support business sponsors in assessing expected ROI, value drivers, adoption assumptions, and operational impacts.
• Partner with Product Owners to prepare discovery outputs for estimation, roadmap planning, backlog creation, and delivery handoff.
• Define adoption considerations early, including process and behavior changes, training needs, stakeholder readiness, and post-launch ownership.
• Help ensure funded solutions are delivered, adopted, measured, and sustained.

Benefits

• Core and optional employee benefits are offered; specific benefits are not listed.
• Variable compensation may include an annual bonus target and long-term incentives for exempt, non-sales roles, subject to plan eligibility and requirements.
• Variable compensation may include overtime, shift differential, and an annual bonus target for non-exempt, non-sales roles, subject to plan eligibility and requirements.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior