CARGO Therapeutics · 7 hours ago

Director, Computational Biology

United States

Full-time

Remote

Director/Executive

3+ years exp

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Responsibilities

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.

Qualification

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Computational BiologyBioinformaticsData AnalysisStatistical MethodsMachine LearningData VisualizationPythonRAzureAWSLinuxNext Generation SequencingCell TherapyImmunology ResearchProject Management

Required

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.