Suzanne Volkert
Head of Global Talent Acquisition Daiichi Sankyo
Seminars
- How can organizations scale TA globally without increasing cost or complexity?
- Learn how Daiichi Sankyo is unifying talent acquisition across the US, Europe, and Japan by standardizing roles, processes, technology, vendors, and employer branding
- The transformation is enabling greater efficiency, clearer recruiter career paths, a consistent global hiring experience, and a stronger enterprise employer brand
This interactive Q&A explores what it takes to fundamentally transform the TA function, from the individual recruiter’s capabilities to the global operating model that supports them.
Drawing on both the AI-enabled recruiter role and the global TA standardization journeys explored in the Discover sessions, participants will examine the strategic choices that determine whether TA becomes a genuine source of competitive advantage.
- How do you build the recruiter capabilities needed for a segmentation and expertise-led TA model?
- What are the hardest trade-offs in building a global TA operating model, and how do you make them?
- How do you use AI to amplify recruiter expertise rather than replace it?
- What does a genuinely strategic TA function look like, and how do you measure it?
The competition for technology and AI talent in life sciences has never been more intense, and the playbooks used to attract and develop scientific talent are not always transferable. This panel brings together senior talent leaders to share how they are evolving their strategies to win in this market: from employer branding and skills-based hiring, to development programs that retain technical talent through the early years and beyond.
Expect frank, experience-led perspectives on what is working and what is not.
- How the tech and AI talent market is evolving, and what life sciences organizations need to do differently to compete
- Building the employer brand and value proposition that resonates with technology and data professionals
- What skills-based hiring and development approaches are proving most effective in practice
- How to build technical career pathways that retain AI and data talent as organizations scale
