Executive Director, Asset Project Leadership

• Collaborate with functional leads across the portfolio to ensure seamless alignment, communication and execution of data-driven strategy from preclinical discovery through clinical development
• Drive and enable a culture of accountability, ownership and innovation aimed at delivering prioritized medicines to patient populations in need
• Partner with key stakeholders including finance and functional line leadership to ensure project resourcing is strategically prioritized and deployed for the most impactful programs & work streams
• Establish and refine processes that maximally leverage Recursion OS and ClinTech insights for advancement of the internal/external drug discovery and development portfolios

You will play a pivotal role ensuring advanced computational approaches and proprietary Recursion advantages are leveraged across the portfolio continuum, redefining traditional paradigms of drug development to ultimately deliver transformative medicines for patients.

• A PhD in life sciences or related scientific discipline with deep expertise in drug discovery & development
• 10+ years of biotech/pharmaceutical industry experience with a proven track record of scientific asset project leadership, progressing drug discovery/development programs through stage-gates using data-driven decision making
• Expertise in cross-functional drug development and in-depth experience leveraging computational approaches to optimize assets
• Deep technical expertise in oncology, strength in additional therapeutic areas such as rare disease and immunology/inflammation a bonus
• Strong resource management and financial acumen

Estimated annual base range of $261,800 to $337,700, plus eligibility for an annual bonus and equity compensation, and a comprehensive benefits package.

Recursion is a clinical stage TechBio company leading the space by decoding biology to radically improve lives through its Recursion OS platform that generates one of the world's largest proprietary biological and chemical datasets and uses sophisticated machine-learning algorithms to advance the future of medicine.