Data Scientist

Responsibilities

• Lead bioinformatic and data science efforts focused on single‑cell RNA‑seq (scRNA‑seq) data, including experimental design support, data processing, quality control, and downstream analysis.
• Apply advanced statistical, machine learning, and AI methods to single‑cell transcriptomic data to identify cell states, trajectories, biomarkers, and mechanistic insights relevant to clinical outcomes.
• Integrate scRNA‑seq data with complementary data types (e.g., bulk RNA‑seq, genomics, clinical metadata) to support translational and clinical decision‑making.
• Analyze and interpret single‑cell TCR sequencing (scTCR‑seq) data to characterize T‑cell clonality, diversity, and clonal dynamics in clinical cell therapy studies.
• Integrate scRNA‑seq and scTCR‑seq data to link T‑cell receptor repertoire features with transcriptional states, phenotypes, and clinical outcomes.
• Design and implement custom analytical tools and models tailored to cell therapy and immunology research questions.
• Collaborate closely with biologists, clinicians, and cross‑functional teams to translate single‑cell analytics into actionable insights for ongoing clinical programs.
• Contribute to the development of analytical models for clinical NGS and single‑cell data in regulated environments.
• Establish and maintain reproducible, scalable data architectures using cloud platforms and/or high‑performance computing resources.
• Build and manage code repositories, documentation, and best practices for single‑cell data analysis.
• Communicate complex analytical methods and findings through clear reports, visualizations, presentations, and collaborative discussions.
• Stay current with emerging single‑cell technologies, methods, and tools, and proactively incorporate them to improve analytical approaches.
• Essential Qualifications, Skills and Experience
• Education & Experience
• 5+ years of relevant experience with a BS/BA,
• or 3+ years with an MS/MA,
• or 1+ year with a PhD
• in data science, computational biology, bioengineering, or a related field, with relevant post‑graduate experience.
• Technical & Scientific Expertise
• Deep hands‑on experience with single‑cell RNA‑seq data analysis, including normalization, batch correction, clustering, annotation, trajectory inference, and differential expression.
• Strong background in NGS workflows, with emphasis on single‑cell experimental platforms and data characteristics.
• Proficiency with single‑cell immune repertoire sequencing concepts, including clonotype definition, diversity metrics, and longitudinal clonal tracking.
• Expertise in bioinformatics and computational biology tools and frameworks commonly used for scRNA‑seq and scTCR‑seq analysis.
• Proficiency in Python and R, including development of reproducible analytical pipelines, workflows, and visualizations.
• Experience working with cloud computing platforms and/or high‑performance computing clusters.
• Solid understanding of statistical methods and their application to single‑cell and biomedical data.
• Domain Experience
• Experience in immunology, immune‑oncology, or cell therapy research is a strong plus.
• Ways of Working & Behaviors
• Team‑oriented mindset with the ability to work independently in a fast‑paced, collaborative environment.
• Strong communication skills, with the ability to explain complex analytical concepts to non‑experts.
• Flexibility to adjust priorities and contribute beyond the initial scope as project needs evolve.
• Date Posted
• 04-jun-2026
• Closing Date

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