Targeted Talent Pools:

• Developed a targeted list of healthcare, biopharma, and enterprise software companies with centralized and mature AI/ML capabilities.
• Focused on organizations known for deploying machine learning at scale, fostering ethical AI practices, and building high-performing data science teams.
• Included leaders from both large corporate and high-growth environments with a proven ability to drive innovation and impact.

Candidate Profile Focus:

• Targeted senior-level AI and ML leaders with experience developing and deploying enterprise-grade solutions across complex, regulated organizations.
• Prioritized candidates who had built machine learning infrastructure from the ground up, led cross-functional teams of 30+ professionals, and scaled AI initiatives globally.
• Sought leaders with the ability to attract top talent, define governance frameworks, and champion the use of AI in business-critical decision-making.

Key Competency Areas:

• Enterprise AI/ML strategy and roadmap development aligned with business goals
• Scalable infrastructure and foundational technology stack for AI enablement
• AI ethics, compliance, and governance frameworks
• Cross-functional collaboration with technology, product, and business stakeholders
• Vendor selection and management across the AI ecosystem

Experience Requirements:

• 15–20+ years of experience in data science, machine learning, or related technical leadership roles
• Experience in regulated industries (e.g., healthcare, life sciences, financial services)
• Proven success building and scaling AI functions, including Centers of Excellence and new capability areas
• Budget and resource management experience; ability to assess in-house vs. outsourced solution models

Evaluation Criteria:

Assessed candidates for AI leadership depth, technology acumen, ethics and governance orientation, strategic communication skills, and the ability to drive measurable business value through advanced analytics.

• Given the strong interest in a role like this one, curated a very targeted list of 50 of the strongest senior AI and data executives from healthcare, biopharma, and enterprise software sectors across North America.
• Conducted direct outreach and in-depth evaluations with more than 30 candidates, aligning each profile to leadership, technical, and organizational fit criteria.
• Presented a ranked shortlist of 7 highly qualified finalists, each with a track record of enterprise AI delivery, ethics-driven leadership, and high-scale team management.

Outcome:
Successfully placed an Executive Director with deep experience leading AI transformation at scale within Fortune 100 and “Big Tech” environments. The selected candidate had built a global AI/ML function from the ground up and was known for balancing strategic vision with operational execution.

Since appointment, the Executive Director has:

• Defined and launched the company’s enterprise AI/ML strategy and roadmap
• Scaled a centralized team of 30+ data scientists, engineers, and AI specialists (with a plan to double in the coming year)
• Established an AI ethics and governance framework aligned with organizational compliance standards
• Enabled enterprise-wide AI adoption through a modern, modular technology stack and reusable solution models