Senior Scientist, Bioinformatics / Computational Biology

Based in Cambridge, MA, this role sits in a collaborative, multidisciplinary environment alongside immunologists, molecular biologists, and data scientists. You will transform complex human and pathogen datasets into clear, decision-driving insights that shape antigen design, patient stratification, and translational strategy across high-priority programs, and you will partner closely with the lab to iterate rapidly.

Accountabilities

• Design, implement, and deliver robust analyses across genomics, bulk and single-cell transcriptomics, and multi-omics to answer program-critical questions with statistical rigor.
• Assemble genomes, call variants, and perform comparative genomics and phylogenetic analyses on bacterial and viral pathogens to inform antigen selection and surveillance strategy.
• Apply machine learning and statistical modeling to discover biomarkers, stratify patients, predict antigen immunogenicity, and forecast treatment response, translating model outputs into actionable program recommendations.
• Build, optimize, and maintain reproducible workflows using HPC schedulers and AWS to scale analyses, reduce turnaround time, and ensure traceability.
• Design and integrate LLM-powered agentic workflows for literature mining, data extraction, and pipeline orchestration to accelerate discovery and improve developer productivity.
• Work closely with experimental scientists to propose computationally informed experiments, interpret results, and refine study designs to improve confidence and reduce cycle time.
• Generate translational insights through differential expression, pathway enrichment, and functional annotation, connecting molecular signals to biological mechanisms and clinical hypotheses.
• Produce publication-quality visualizations and reports, present findings clearly to cross-functional stakeholders, and champion version control, workflow managers, and reproducible research practices to strengthen code quality and method sharing across programs.
• Stay current with emerging tools in bioinformatics, AI/ML, and agentic AI, piloting new approaches, sharing learnings, and scaling successful methods across the portfolio.

Essential Skills And Experience

• PhD in Bioinformatics, Computational Biology, Genomics, Molecular Biology, Computer Science, or a closely related quantitative discipline, with 2–5 years of industry experience; alternatively, an MS in a relevant discipline with 4–6 years of industry experience in bioinformatics, computational biology, or genomics.
• A demonstrated track record of independent research through publications, conference presentations, or successful project delivery.
• Proficiency in R and/or Python for genomic data analysis, statistical computing, and data visualization, including tools such as ggplot2, Bioconductor, tidyverse, pandas, and scikit-learn.
• Hands-on experience with NGS data analysis, including alignment tools such as STAR, BWA, and Bowtie2; quantification tools such as Salmon, featureCounts, and HTSeq; and variant calling tools such as GATK and bcftools.
• Familiarity with RNA-seq analysis workflows, including differential expression methods such as DESeq2, edgeR, and limma, as well as pathway analysis and gene set enrichment approaches such as ssGSEA and MSigDB.
• Experience working in Linux/Unix environments and with HPC job schedulers such as SLURM, SGE, or PBS, and/or cloud computing platforms such as AWS or GCP.
• Working knowledge of Git/GitHub and reproducible research practices, including Nextflow or similar workflow managers.
• Solid understanding of molecular biology fundamentals, genome annotation, and public bioinformatics databases such as NCBI, Ensembl, UniProt, and PDB.
• Foundational knowledge of machine learning concepts and applied statistics relevant to biomarker discovery and genomic data.
• Strong analytical thinking, creative problem-solving, and the ability to translate complex datasets into actionable biological insights.
• Excellent written and verbal communication skills, a collaborative mindset, intellectual curiosity, and the ability to manage multiple priorities and deliver results within timelines.

Desirable Skills And Experience

• Experience in at least one therapeutic area—infectious diseases, oncology, or inflammatory disease.
• Experience with comparative genomics and microbial or viral genome analysis, including pangenome methods, AMR gene detection, and phylogenetics.
• Building predictive and prognostic models using supervised and unsupervised machine learning methods on clinical or preclinical omics data.
• Familiarity with deep learning frameworks such as PyTorch and TensorFlow.
• Exposure to biological foundation models such as ESM, EvolutionaryScale, scGPT, TranscriptFormer, and Evo.
• Experience with or strong interest in agentic AI workflows for bioinformatics, including LLM-orchestrated pipelines, retrieval-augmented generation (RAG) for scientific literature, and tool-using AI agents that interact with databases and analysis tools.
• Proficiency with AI-assisted coding tools such as Claude Code or GitHub Copilot.
• Exposure to single-cell RNA-seq tools such as Seurat, Scanpy, and CellRanger.
• Knowledge of structural biology tools, protein modeling, or antigen/antibody design.
• Experience with containerization and infrastructure-as-code.
• Familiarity with LLM APIs and prompt engineering for scientific applications, including structured output generation and multi-agent system design.

Why AstraZeneca

At AstraZeneca, ambitious science meets everyday collaboration. Here, bioinformaticians, immunologists, clinicians, and engineers come together to share knowledge openly, challenge ideas constructively, and learn from setbacks as they work toward better solutions. You will contribute across diverse therapy areas, with visibility into decisions that matter and support from leaders who encourage experimentation and innovation. We pair rigorous scientific standards with creativity and value kindness alongside ambition. Most importantly, we connect each individual’s contribution to a clear purpose: translating insights into medicines that can change patients’ lives. If you are ready to turn data, models, and modern AI into faster, smarter decisions for patients, we encourage you to apply and show us how you can make an impact from day one.

Pay

The annual base pay for this position ranges from $115,992.00 - $172,671.60. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles.

Benefits

Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans.

Schedule

Date Posted 11-Sep-2026 Closing Date 13-Sep-2026