Director, Computational Biology

November 27

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CARGO Therapeutics

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2021

🧬 Biotechnology

💊 Pharmaceuticals

🔬 Science

🔥 Funding within the last year

💰 Post-IPO Equity on 2024-05

Description

• Establish strong partnerships with the IT and Data Science teams to develop and manage data infrastructure, including database architecture, data storage, and security protocols. • Maintain proficiency in utilizing Azure or AWS cloud computing environment for data analysis and management, ensuring integration with existing infrastructure and workflows. • Collaborate closely with cross-functional teams (research, manufacturing, clinical, data science) by providing guidance on data generation and curation to enable subsequent pull through and data science analyses. • Partner with the biostats team to develop strategies for multi-variate analyses that incorporate clinical outcomes into data sets. • Utilize advanced statistical and computational methods to analyze large-scale datasets generated from research screening efforts, identifying key trends, patterns, and potential biomarkers. • Develop and implement robust data analysis pipelines and algorithms to streamline data processing, quality control, and visualization in research. • Contribute and potentially initiate the use of innovative technologies such as AI, Machine Learning, LLM. • Integrate emerging technologies and methodologies in genomics, bioinformatics, and data science fields, into existing workflows and advise teams on how to incorporate. • Effectively communicate findings and insights through presentations, reports, and publications, fostering a collaborative and data-driven culture within the organization.

Requirements

• Master's or Ph.D. degree in bioinformatics, computational biology, computer science, statistics, or a related field with 3+ post-graduate years of experience. • Familiarity with next generation sequencing is a plus (sample preparation, library generation, etc). • Guide teams on preferred methods for high quality data generation. • Proficiency in programming languages commonly used in data analysis, such as Python or R, as well as experience with bioinformatics tools and packages. • Strong understanding of statistical methods, machine learning techniques, and data visualization principles, with the ability to apply them to biological datasets. • Familiarity with cloud computing platforms, particularly Azure (or AWS), for data analysis and management, as well as experience working in a Linux environment. • Excellent interpersonal and communication skills, with the ability to collaborate effectively with cross-functional teams and stakeholders. • Proven track record of independently driving projects from conception to completion, with a focus on delivering actionable insights and solutions. • Prior experience in cell therapy or immunology research is a plus, but not required.