Manager, Computational Biology (Early Oncology)

Recursion•Salt Lake City, UT

1d•Hybrid

About The Position

As a Manager within Recursion's partnership-facing data science team, you will be at the forefront of reimagining drug discovery from first principles. You will lead a team of world-class computational biologists focused on identifying and advancing the next generation of oncology therapeutics. You will act as a "player-coach," balancing direct technical contribution with the mentorship and strategic leadership of a high-performing team. Your mission is to integrate Recursion’s massive datasets—phenomics, transcriptomics, and proteomics—to nominate novel targets, validate disease biology, and define the precision oncology strategies that ensure our medicines reach the right patients.

Requirements

PhD in a quantitative field (Computational Biology, Bioinformatics, Statistics, Cancer Biology, etc.) with 5+ years of experience in biotech or pharma industry OR MS in a relevant field and 7+ years of experience in biotech or pharma industry solving fundamental problems in oncology or drug discovery.
Proven track record of managing and developing direct reports within a scientific or technical environment.
Deep understanding of cancer biology, including experience with biomarker discovery and patient population stratification.
Experience with two or more oncology areas; strong understanding of patient genetics and historical druggability of disease relevant pathways
Deep expertise in the analysis and data integration of two or more ‘omics data modalities (phenomics, transcriptomics, proteomics, genomics), including experience working with patient data
Exceptional data visualization skills
Advanced skills in Python or R for the analysis of high-dimensional biological data (e.g., transcriptomics, proteomics, or high-content imaging).
Ability to distill complex technical concepts into clear and compelling narrative for internal and external-cross functional audiences.

Nice To Haves

Familiarity with large-scale oncology datasets such as TCGA, CCLE, DepMap, and/or Real-World Data (RWD).
Experience designing high-throughput screens or CRISPR/small-molecule perturbations to validate therapeutic hypotheses.
Exposure to the requirements for IND-enabling studies or clinical trial biomarker analysis

Responsibilities

Direct and mentor a team of data scientists and computational biologists, fostering a culture of scientific rigor, bold experimentation, and continuous professional growth.
Lead the design and execution of analyses for target nomination and validation, using Recursion’s platform to identify novel vulnerabilities in cancer biology.
Develop biomarker strategies and patient-stratification hypotheses to support programs as they progress from nomination through hit-to-lead and lead-optimization.
Act as a key "connector," leading your team to pilot innovative analysis methods and collaborating with platform and engineering teams to productionalize and scale these tools for organization-wide impact.
Maintain a 50% individual contribution (IC) load, performing complex data integration and analysis to solve "killer questions" within the oncology portfolio.
Partner with biologists, medicinal chemists, and clinical leads to build compelling data packages that drive program milestones and investment decisions.
Present data analysis to external decision makers and stakeholders in a clear and compelling way that drives toward getting medicines to patients.