Data Scientist

AstraZeneca

2d

About The Position

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company dedicated to discovering, developing, and commercializing prescription medicines for some of the world’s most serious diseases. The company strives to be a Great Place to Work, empowering employees to push the boundaries of science, challenge convention, and unleash their entrepreneurial spirit. AstraZeneca is committed to embracing differences and taking bold actions to drive change for global healthcare and sustainability challenges. The company fosters an inclusive culture where diverse thinking generates new and valuable opportunities, with a commitment to lifelong learning, growth, and development for all. The Inclusion & Diversity (I&D) mission is to create an inclusive and equitable environment where people belong, leveraging diversity to advance science and deliver life-changing medicines. This role is centered around contributing to this mission by leading bioinformatic and data science efforts, specifically focused on single-cell RNA-seq (scRNA-seq) data, to generate actionable insights for ongoing clinical programs.

Requirements

• 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.
• 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.
• 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.

Nice To Haves

• Experience in immunology, immune‑oncology, or cell therapy research is a strong plus.

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.

Benefits

• An inclusive environment where equal employment opportunities are available to all applicants and employees.
• An inclusive and equitable environment where people belong, using the power of our diversity to push the boundaries of science to deliver life-changing medicines to patients.
• Commitment to lifelong learning, growth and development for all.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees