Tifani McCann is Vice President of Data and Analytics at Otsuka Pharmaceutical, where she leads enterprise data and AI strategy to support innovation and improved patient outcomes. Her career has been shaped by a strong foundation in problem-solving, rooted in an early interest in puzzles that evolved into a passion for using data to inform real-world decisions.
Tifani began her professional journey after earning a PhD in Biostatistics, joining Bristol-Myers Squibb (BMS) as a protocol statistician. Over a 17-year tenure, Tifani held a range of leadership roles, including leading biometrics therapeutic areas, business operations teams, and the enterprise clinical data organization. These experiences enabled her to expand from deep technical expertise into broader enterprise leadership.
Her career path reflects what she describes as a “career lattice,” with each role offering opportunities to develop new skills and domain knowledge. Along the way, Tifani has led high-performing technical teams, building a reputation as a leader who actively advocates for her teams and ensures their contributions are recognized.
In 2016, Tifani joined Covance in a global leadership role with significant P&L responsibility, where she led two major transformation initiatives and gained further experience in business and operational leadership. She returned to the pharmaceutical industry in 2019, joining Otsuka to lead and develop its enterprise data and AI strategy.
Tifani’s leadership is grounded in a commitment to translating data into meaningful impact, particularly in advancing solutions that improve patient care.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“Effective data and AI leaders must connect data capabilities to business priorities, communicate complex ideas simply, create clarity out of ambiguity and build strong cross functional relationships. They must build credibility with both technical and non-technical colleagues. Therefore, having technical depth matters, but so does the ability pivot, relate in non-technical terms and understand the needs of business partners.
“Moreover, effective data and AI leaders balance curiosity with disciplined execution to turn innovative concepts into meaningful business impact.”
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“Be as deeply interested in people as you are in data. Technical mastery opens doors, but understanding motivations, perspectives, and relationships ultimately shapes your effectiveness as a leader.”