Job Description: We are seeking a highly motivated and collaborative Bioinformatics Scientist to support oncology drug discovery programs through advanced computational analysis and biological interpretation of large-scale omics datasets. The successful candidate will partner closely with discovery teams to derive biological insights from NGS and multi-omics data contribute to experimental design and enable data-driven decision-making across early- and late-stage programs.
Responsibilities: - Support oncology research by analysing high-throughput omics data including RNAseq WES and other NGS platforms.
- Query public and internal cancer genomics resources to assess mutation/expression distributions and clinical relevance.
- Integrate and interpret internal datasets (e.g. transcriptomics proteomics single-cell spatial omics) to uncover mechanisms of disease and therapeutic response.
- Communicate analytical findings and recommendations effectively to cross-functional teams with diverse scientific backgrounds.
- Collaborate with experimental and discovery scientists to optimize study designs and identify computational opportunities.
- Develop and maintain reproducible bioinformatics workflows and pipelines.
- Leverage cloud (AWS) and/or HPC infrastructure for scalable data analysis.
- Stay current with emerging technologies and data repositories to enhance data interpretation.
Requirements: - Ph.D. in Bioinformatics Computational Biology Genomics Cancer Biology or related field; OR.
- Masters degree with 1 3 years of relevant industry experience; OR.
- Bachelors degree with 6 8 years of relevant experience.
- Demonstrated oncology background preferably with exposure to immuno-oncology immunology or cancer genomics.
- Hands-on experience with NGS data analysis (e.g. RNAseq WES) from raw data processing to downstream interpretation.
- Proficiency in R (including ggplot2); competence in Python is preferred.
- Experience working in Linux environments and using HPC clusters or cloud platforms (AWS).
- Strong data visualization and presentation skills.
- Excellent written and verbal communication skills.
- Strong team orientation and ability to work in cross-functional settings.
- Experience with single-cell RNA-seq spatial omics CRISPR screens or proteomics data.
- Familiarity with public data repositories such as TCGA GTEx GEO ENA/EBI and GDC.
- Prior industry experience in pharmaceutical or biotech settings.
- Experience supporting drug discovery programs from early to late stages.