Vice President, Translational Data Science, Computational Biology

Summary

Join Recursion as the Vice President, Translational Data Science, and lead the strategy and implementation of connecting data from genome-scale -omics platforms with population- and patient-derived genetics. You will leverage advanced analytics, including ML/data science, to identify and validate target selection, disease and patient linkages, and drive precision medicine. Responsibilities include leading the industrialization of identifying diseases and patient populations, integrating machine learning methods, identifying optimal disease and patient linkages, developing computational tools, integrating patient data from clinical trials, collaborating with cross-functional leaders, guiding teams of computational biologists and data scientists, and recruiting and managing high-performing teams. Success will be defined by the impact on the industrialization of program initiation and progression to development with validated biomarker strategies. The role reports to the SVP Clinical Development & Data Science and involves collaboration with peer leaders across various disciplines. The position is open to remote work with regular on-site visits.

Requirements

• 7+ years applying expertise in computational biology leveraging the latest techniques in ML across drug discovery and development
• Key areas of prior experience include addressing problems in functional and statistical genetics with high-dimensional -omics data, particularly aimed at problems in target identification, mechanistic fine-mapping, as well as biomarker identification and development in precision medicine to enable patient stratification and response prediction
• A track-record for pairing large-scale patient/population datasets in a closed loop with high-throughput in vitro functional genomics and machine learning to transform the process of identifying targets, models, and biomarkers with patient connectivity and validity
• Experience in developing and implementing patient stratification / precision medicine solutions in clinical development leveraging multi-omics and clinical data and well versed in regulatory considerations
• Experience hiring, managing, and mentoring multiple teams engaged in drug discovery activities in a matrixed environment
• Curiosity and the professional skill-set to excel in an open, highly collaborative, and growth-oriented environment

Responsibilities

• Lead the strategy and execution to industrialize the process of identifying diseases and patient populations through novel gene-compound inferences informed by population-scale forward genetics and genome-scale reverse genetics data
• Integrate advanced machine learning methods to connect genetic insights across monogenic and polygenic conditions, ensuring that these discoveries are translated into actionable strategies for patient stratification, clinical trial design, and regulatory engagement across the entire drug development lifecycle
• Lead the strategy and implementation efforts to identify optimal disease and patient linkages to our -omics phenotypes, along with the discovery and validation of translational biomarkers and patient selection solutions to drive precision medicine for our therapeutic programs
• Drive the development and implementation of new computational tools including ML/DS approaches, algorithms, and methodologies
• Drive the integration of patient genetic and biomarker data collected in Recursion’s clinical trials to enable reverse translation , bridging clinical insights back into discovery programs
• Be a key member to contribute to strategy for data and diagnostic partnerships in support of the Recursion OS and clinical portfolio
• Collaborate closely with leaders in discovery biology, chemistry, and clinical sciences to accelerate the translation of data-driven insights into tangible therapeutic advancements
• Establish strong cross-functional partnerships to ensure that computational biology efforts are deeply integrated into the therapeutic area strategies
• Guide teams of computational biologists and data scientists in executing the above strategy to industrialize the process of turning maps into medicines
• Recruit, mentor, and manage high-performing teams of computational biologists and data scientists working in our therapeutic areas (oncology, neuroscience, and more) as well as on pan-therapeutic area initiatives, including genetics work

Preferred Qualifications

Making one of our offices your home base is preferred – London, New York City, or Salt Lake City

Benefits

• Bonuses and equity compensation
• Comprehensive benefits package for United States based candidates
• Remote work