Scientist/Sr. Scientist, Bioinformatics Data

Scientist/Sr. Scientist, Bioinformatics Data Legend Biotech is a global biotechnology company dedicated to treating, and one day curing, life-threatening diseases. Headquartered in Somerset, New Jersey, we are developing advanced cell therapies across a diverse array of technology platforms, including autologous and allogenic chimeric antigen receptor T-cell, T-cell receptor (TCR-T), and natural killer (NK) cell-based immunotherapy. From our three R&D sites around the world, we apply these innovative technologies to pursue the discovery of safe, efficacious and cutting-edge therapeutics for patients worldwide. Legend Biotech is seeking a Scientist/Sr. Scientist, Bioinformatics Data as part of the Early Drug Development team based in Somerset, NJ. Role Overview 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. Key Responsibilities Data Analysis: 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. Pipeline Development & Automation: 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. Cross-Functional Collaboration: 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. Proven ability to thrive in a fast-paced environment, manage multiple projects simultaneously, and pivot quickly based on data-driven feedback. Exceptional critical thinking skills with a knack for debugging complex code and parsing unstructured data formats. Creative, innovative and excellent communication and presentation skills. This role is designed as the starting point of group effort to solve complex biological and clinical problems in a fast paced environment. We look for individuals who take extreme ownership of their expertise and training, and driven by the prospect of turning data into information, and information into knowledge. Legend Biotech