Job Locations US-MA-Boston | US-Remote | US-WA-Seattle | US-NH-Portsmouth | US-TX-Plano

ID

2026-74432

Position Type

Full-Time

Job Grade

21

Department

0001-12528 Enterprise Data and Data Science

Market

Corporate Center

Referral Bonus Amount

2,500

Minimum Salary

USD $179,000.00/Yr.

Maximum Salary

USD $322,000.00/Yr.

Typical Starting Salary

$214,800 - $286,300

Recruiter

Roy Ruhling

Internal Application Deadline

3/6/26

We’re seeking a mission-driven and strategic leader to join our Enterprise Data & Data Science organization as Senior Director and leader of our Enterprise Data Science team. This high-impact role sits at the center of our enterprise AI/ML efforts — overseeing the platforms, standards, and responsible innovation practices for our Data Science & Machine Learning Engineering community that enable scalable, secure, and ethical use of machine learning and AI across the company.

As a senior member of our rapidly growing Data & Data Science community, you’ll drive the strategy for enterprise enablement — spanning AI/ML platform product leadership, governance expertise to fuel our Responsible AI program, setting the standard for how Data Science is done at the company, and being a leader of cross-functional/cross business efforts. You will also serve as a champion for our data science community of practice, helping foster connection, career growth, and shared best practices across disciplines.

Key Responsibilities:

• Product Leadership for AI/ML Infrastructure
  Own the product strategy and roadmap for our enterprise ML platform — including MLOps tooling, model lifecycle management, LLMOps for Data Scientists, observability, and additional AI/ML developer enablement frameworks.

• Enterprise Standards
  Define and evolve our enterprise standards for scalable, secure, and responsible AI development. Set our preferred processes spanning technology, skills, and training for building/evaluating/deploying/monitoring AI/ML and ensure we integrate observability and trust at every level. Drive alignment across engineering, data science, architecture, and business teams.

• Leading AI Innovation
  Lead a talented team of data scientists to produce cutting edge research and capabilities in the rapidly evolving AI space. Understand and communicate the art of possible, and lead efforts to accelerate our AI work through the design, implementation, and communication of emerging tools and packages to supercharge our Data Science/ML Engineering community.

• AI Governance & Risk Integration
  Partner with Enterprise Risk, Legal, Compliance, and Business teams to operationalize Responsible AI — translating ethical and regulatory principles into enterprise-scale governance practices.

• Leadership of the Data Science Community
  Serve as a leader for our cross-functional data science community. Enable knowledge sharing, talent development, and community-building across teams and business lines.

• People Leadership & Team Building
  Lead and grow a high-performing team of product managers, scientists, and platform strategists. Foster a culture of experimentation, ownership, and inclusivity. Mentor senior talent and help shape the next generation of AI leaders.

• Cross-Functional Influence
  Act as a trusted partner to executive leadership. Communicate complex scientific, technical, and governance strategies clearly to non-technical stakeholders, and champion AI as a strategic differentiator across the enterprise.

• 10+ years of experience in product leadership, technology strategy, or AI/ML platform development in large, complex organizations.
• Deep understanding of AI/ML systems architecture, MLOps, and emerging technologies such as LLMs, vector search, and prompt orchestration.
• Proven track record delivering enterprise-grade platforms and governance processes for AI or other high-risk technologies and leading highly nuanced change management efforts to ensure impact.
• Experience leading and engaging data science and technical communities across a federated enterprise. Comfort operating in a matrixed organizational structure.
• Strong people leadership skills with a history of mentoring, scaling, and retaining high-performing teams.
• Excellent communication and influence skills — able to align cross-functional stakeholders from technical, regulatory, and business domains.

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