Associate Principal Bioinformatics Specialist, Omics, Oncology Data Science Platforms

Associate Principal Bioinformatics Specialist, Omics, Oncology Data Science Platforms

Introduction to role

Are you an expert in bioinformatics pipelines, AI and data engineering workflows for biomarker discovery? Are you an AI-native bioinformatician who leverages LLMs/Foundation Models to improve your productivity and augment your workflows? Do you want to make a significant impact on cancer research by applying your knowledge in a company that transforms scientific ideas into life-changing medicines? If so, AstraZeneca could be your next career destination!

Accountabilities

Join our growing ODSP team to support AstraZeneca Oncology's strategic initiatives in high-throughput molecular data generation, including somatic DNA sequencing, single-cell and bulk transcriptomics, proteogenomics, and digital pathology. As an AI-native Bioinformatician with expertise in NGS 'omics data, you'll design and apply innovative computational & AI analysis methods to advance our multi-omics research portfolio. Your strong quantitative skills will help build scalable solutions to interrogate diverse cancer 'omics datasets, empowering researchers to use AI systems for data-driven decision-making and biomedical knowledge generation.

Essential Skills/Experience​

• Master’s degree in Bioinformatics, Computational Biology, or a related field with 5+ years of applied experience in bioinformatics data analysis or Ph.D. in Bioinformatics, Computational Biology, or a related field with 2+ years of experience 

• Deep understanding of at least one type of molecular profiling data (e.g. RNA or DNA sequencing) and experience in analysing human Illumina NGS results from raw data to insights 

• Direct experience with domainspecific foundation models for omics or imaging (e.g., finetuning, modality adaptation), with strong understanding of transformers/neural networks

• Extensively uses AI tools for productivity like LLMs, coding copilots (e.g. Github copilot with VS Code) and research assistants 

• Familiarity with Agentic frameworks (e.g. LangChain, Pydantic AI) and their application to scientific problems 

• Experience with other machine learning, graph modelling, Bayesian analytics or other non-traditional approaches to model biological data for biomarker discovery 

• Proven programming skills, (Python preferred) and familiarity with software development best-practices (end-to-end tests, unit testing, version control with git) 

• Experience working in Unix/Linux environments, exposure to at least one common workflow language such as Nextflow or Snakemake, familiarity with package management (e.g. Conda) 

• Cloud computing (preferably AWS), and High-Performance Computing (HPC) 

• ‘Builder’ mindset, strategic thinker, and experience leading projects

• Strong, professional communication skills and excellent attention to detail, capable of developing good effective collaborative relationships with diverse teams of technical and non-technical analysts, engineers, scientists, strategists 

• Experience working within a team environment ​

Desirable Skills/Experience

• Proficiency analysing and interpreting data from multiple 'omics platforms (NGS sequencing, transcriptomics, epigenomics, genomics, proteomics etc.) in an oncology context 

• Exposure to public cancer knowledgebases and resources (e.g. dbSNP, COSMIC, gnomAD, GDC, TCGA, 1000 Genomes etc)

• Experience working with patient data from clinical trials and biomarker development 

• Well networked within external bioinformatics, NGS, and AI/ML communit