Sr. Scientist, Bioinformatics Data

About the role

Legend Biotech is a global biotechnology company dedicated to treating and, one day, curing life-threatening diseases. Headquartered in Bridgewater, New Jersey, we are advancing the next generation of cell therapy through a portfolio of innovative technologies, including autologous, allogeneic, and in vivo cell therapy approaches. Our research spans chimeric antigen receptor T-cell (CAR-T), T-cell receptor (TCR-T), natural killer (NK) cell-based therapies, and other emerging platforms designed to transform the treatment of serious diseases. From our global network of research and development sites, we are committed to discovering and developing safe, effective, and cutting-edge therapies for patients worldwide. Legend Biotech entered into a global collaboration agreement with Johnson & Johnson to jointly develop and commercialize CARVYKTI® (ciltabtagene autoleucel; cilta-cel). Through this strategic partnership, we combine complementary expertise and capabilities to advance innovative immunotherapies for patients living with multiple myeloma.

Legend Biotech is seeking a Scientist/Sr. Scientist, Bioinformatics Data as part of the Early Drug Development team based in Somerset, NJ. We are seeking a highly motivated, passionate, and driven Bioinformatics Data Scientist with high scientific curiosity to join our research and development team. In this role, you will bridge the gap between complex biological datasets and actionable therapeutic insights. You will design, develop, and execute scalable computational pipelines to analyze high-dimensional genomic data. The ideal candidate possesses a deep curiosity for biological systems, an analytical mindset, and the technical skillset to tackle unstructured, diverse and complex multiomics challenges. Whether you come from a deep biological background with strong computational skills or a data science background with a proven track record in working with biological data, you will play a critical role in accelerating both our discovery and clinical pipeline.

Responsibilities

• Analyze diverse and large-scale genomic datasets (e.g., RNA-seq, scRNA-seq, WES/WGS, epigenetic, or multi-omics data) to identify biomarkers, therapeutic targets, or disease mechanisms.
• Apply advanced statistical, machine learning, and data-mining techniques to extract meaningful patterns from noisy biological data.
• Perform quality control, normalization, and batch-correction across heterogeneous datasets.
• Design, optimize, and maintain robust, scalable bioinformatics pipelines.
• Implement version-controlled code architectures to ensure reproducibility and scalability of data analyses.
• Procure and integrate existing biological databases with internal datasets.
• Translate complex computational and statistical findings into clear biological narratives for experimental biologists, clinicians, and stakeholders.
• Collaborate with IT and other functional groups.

Requirements

• Ph.D. or M.S. in Bioinformatics, Computational Biology, Data Science, Genomics, Biology, or a highly quantitative field.
• Proven experience handling genomic data (Next-Generation Sequencing/NGS data analysis is required).
• Ability to turn raw biological data into structured insights.
• Strong experience with AI application in data science.
• Advanced proficiency in R (e.g., Bioconductor, Tidyverse) and/or Python (e.g., Pandas, NumPy, Scikit-learn).
• Experience with standard bioinformatics tools (e.g., alignment tools, variant callers, single-cell toolkits like Seurat/Scanpy).
• Experience with cloud computing platforms (AWS, GCP) and containerization (Docker, Singularity) is a strong plus.
• A self-starting attitude with an intrinsic desire to stay ahead of the curve in emerging computational methods and biological technologies.