Bioinformatics Scientist-Biology at Zealand Pharma in Cambridge, MA

Summary: Zealand Pharma is a biotechnology company focused on advancing medicines for obesity and metabolic health. The Bioinformatics Scientist – Biology role provides bioinformatics support to the Global Biology research team, driving analysis and integration of multi-omics datasets to inform program decisions and building scalable computational pipelines. Responsibilities: - Provide bioinformatics support to Global Biology project teams across discovery-to-clinic activities, translating biological questions into fit-for-purpose analyses - Analyze, integrate, and interpret multi-omics datasets (e.g., transcriptomics, genomics, proteomics) to generate clear, decision-driving insights - Develop, implement, and maintain reproducible computational pipelines and analysis workflows for data integration and downstream interpretation - Collaborate with external partners to co-develop tools, pipelines, and best practices, including incorporation of machine learning/artificial intelligence approaches where relevant - Partner cross-functionally with Chemistry, Drug Metabolism and Pharmacokinetics/Safety, Formulation, and Clinical stakeholders to ensure analyses address key development questions - Communicate results through clear visualizations, summaries, and presentations tailored to both scientific teams and senior/executive audiences Required Qualifications: - Ph.D. in Bioinformatics, Computational Biology, Genomics, or a related field - 0–3+ years of relevant experience in biotech/pharmaceutical industry or equivalent translational research experience - Demonstrated ability to analyze and integrate multi-omics data, including transcriptomics, genomics, and proteomics - Experience developing computational pipelines/tools for data processing, integration, and analysis (with an emphasis on reproducibility) - Exposure to or experience with machine learning/artificial intelligence methods applied to biological datasets - Strong communication and presentation skills, with ability to explain complex analyses to cross-functional and senior stakeholders Required Skills: Bioinformatics, Multi-omics data analysis, Transcriptomics, Genomics, Proteomics, Computational pipeline development, Data integration, Machine learning, Artificial intelligence