Associate Principal Bioinformatics Specialist, Omics, Oncology Data Science Platforms

Role Summary

Associate Principal Bioinformatics Specialist, Omics, Oncology Data Science Platforms. The role focuses on bioinformatics pipelines, AI and data engineering workflows for biomarker discovery, leveraging AI-native approaches and Foundation Models to improve productivity and augment workflows, with a goal of advancing cancer research and biomarker discovery.

Responsibilities

• 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.
• Design and apply innovative computational and AI analysis methods to advance the multi-omics research portfolio.
• Develop scalable solutions to interrogate diverse cancer omics datasets and enable data-driven decision-making and biomedical knowledge generation.

Qualifications

• Required: 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 analyzing human Illumina NGS results from raw data to insights.
• Direct experience with domain-specific foundation models for omics or imaging (e.g., fine-tuning, modality adaptation) and strong understanding of transformers/neural networks.
• Extensive use of AI tools for productivity (LLMs, coding copilots, research assistants).
• Familiarity with Agentic frameworks (e.g., LangChain, Pydantic AI) and their application to scientific problems.
• Experience with machine learning, graph modeling, Bayesian analytics or other non-traditional approaches to modeling 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 workflow languages (Nextflow or Snakemake), and familiarity with package management (Conda).
• Cloud computing experience (preferably AWS) and High-Performance Computing (HPC).\n
• Builder mindset, strategic thinker, and experience leading projects.
• Strong, professional communication skills and ability to build collaborative relationships with diverse teams of technical and non-technical analysts, engineers, scientists, and strategists.

Skills

• Experience analyzing and interpreting data from multiple omics platforms (NGS sequencing, transcriptomics, epigenomics, genomics, proteomics) in an oncology context.
• Exposure to public cancer knowledgebases and resources (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 communities.