$ cat jobs/director-data-science-formation-bio-d6ff80e27bb6.json
Director, Data Science
About Formation Bio Formation Bio is a tech and AI driven pharma company differentiated by radically more efficient drug development. Advancements in AI and drug discovery are creating more candidate drugs than the industry can progress because of the high cost and time of clinical trials. Recognizing that this development bottleneck may ultimately limit the number of new medicines that can reach patients, Formation Bio, founded in 2016 as TrialSpark Inc., has built technology platforms, processes, and capabilities to accelerate all aspects of drug development and clinical trials. Formation Bio partners, acquires, or in-licenses drugs from pharma companies, research organizations, and biotechs to develop programs past clinical proof of concept and beyond, ultimately helping to bring new medicines to patients. The company is backed by investors across pharma and tech, including a16z, Sequoia, Sanofi, Thrive Capital, John Doerr, Spark Capital, SV Angel Growth, and others. You can read more at the following links: Our Vision for AI in Pharma Our Current Drug Portfolio Our Technology & Platform At Formation Bio, our values are the driving force behind our mission to revolutionize the pharma industry. Every team and individual at the company shares these same values, and every team and individual plays a key part in our mission to bring new treatments to patients faster and more efficiently. About the Position As the Director of Data Science at Formation Bio, you will be at the forefront of revolutionizing drug development through AI and advanced analytics. In this role, you'll lead crucial initiatives that directly impact our drug development portfolio, from developing sophisticated models for patient selection to creating AI-powered solutions for clinical trial optimization. You'll work at the intersection of computational biology, machine learning, and drug development, collaborating with cross-functional teams to translate complex biological data into actionable insi
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