Data and AI Capabilities Lead

Boston Scientific • Arden Hills, MN

2d • $106,800 - $202,900 • Hybrid

About The Position

The Data and AI Capabilities Lead identifies, shapes, and advances high-value opportunities that apply data, generative AI, agentic AI, and reusable AI capabilities to business problems. Working at the intersection of business strategy, data, AI, product discovery, and technology delivery, the role partners with divisions, regions, and functions to develop early ideas into investment-ready opportunities with clear value, feasibility, data readiness, adoption needs, and fit with reusable capabilities.

The role 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 with Product Owners, AI Core Services, data teams, architecture, security, engineering, and business stakeholders to help select appropriate opportunities for delivery and position funded solutions to achieve business impact.

The position follows a hybrid work model, requiring employees to be in a local office at least three days per week. Relocation assistance and employment visa sponsorship are not available for this position.

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 their application in enterprise use cases.
• Strong understanding of data and AI concepts, including generative AI, large language models, agentic AI, analytics, data platforms, integrations, and enterprise data readiness.
• Technical fluency and curiosity, including the ability to engage with engineers and architects about APIs, MCPs, integrations, data flows, application architecture, and system dependencies.
• Interest in emerging AI technologies and real-world applications, and ability to learn unfamiliar technologies, tools, and concepts quickly.
• Demonstrated ability to partner 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 resides, how usable it is, and how data quality, governance, or access may affect feasibility.
• Strong facilitation, communication, and executive presence, with 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 operating in ambiguity and bringing structure to 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.
• Serve as a strategic Data and AI thought partner, helping stakeholders understand AI capabilities, data readiness considerations, and when AI may not be the right solution.
• Identify similar needs across business areas and help combine, redirect, or scale opportunities to avoid duplicative one-off 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 the data required for opportunities, where it resides, whether it is landed, governed, accessible, and usable, and whether gaps or quality issues affect feasibility or value.
• Partner with data teams, 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 ensure discovery outputs support estimation, roadmap planning, backlog creation, and delivery handoff.
• Define adoption considerations early, including business process and user behavior changes, training needs, stakeholder readiness, and post-launch ownership.
• Help ensure funded solutions are designed to be delivered, used, adopted, measured, and sustained.

Benefits

• Annual bonus target and long-term incentives may be available for eligible exempt, non-sales roles, subject to plan eligibility and other requirements.
• Variable compensation, including overtime and shift differential, and an annual bonus target may be available from time to time for eligible non-exempt, hourly, non-sales roles, subject to plan eligibility and other requirements.

What This Job Offers

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