Senior Scientist, Bioinformatics / Computational Biology

Are you ready to harnessmulti-omics,comparative genomics, andagentic AI to accelerate vaccines and immune therapies from discovery to the clinic? In this role, you will transform complex human and pathogen datasets into clear, decision-driving insights that shapeantigen design,patient stratification, andtranslational strategy across high-priority programs.

Based inCambridge, MA you will work in a collaborative, multidisciplinary environment alongsideimmunologists,molecular biologists, anddata scientists. If you thrive at the intersection of computation and experiment-designing reproducible pipelines onHPC and cloud platforms while partnering closely with the lab to iterate rapidly-this role offers the opportunity to influence study design, guidego/no-go decisions, and help advance novel immune-based therapies toward patients.

Accountabilities

• You will design, implement, and deliver robust analyses acrossgenomics,bulk and single-cell transcriptomics, andmulti-omics to answer program-critical questions with statistical rigor. You will assemble genomes, call variants, and performcomparative genomics andphylogenetic analyses on bacterial and viral pathogens to inform antigen selection and surveillance strategy.
• You will applymachine learning and statistical modeling to discover biomarkers, stratify patients, predict antigen immunogenicity, and forecast treatment response, translating model outputs into actionable program recommendations. You will also build, optimize, and maintain reproducible workflows usingHPC schedulers andAWS to scale analyses, reduce turnaround time, and ensure traceability.

In addition, you will design and integrateLLM-powered agentic workflows for literature mining, data extraction, and pipeline orchestration to accelerate discovery and improve developer productivity. Working closely with experimental scientists, you will propose computationally informed experiments, interpret results, and refine study designs to improve confidence and reduce cycle time.

You will generate translational insights throughdifferential expression,pathway enrichment, andfunctional annotation, connecting molecular signals to biological mechanisms and clinical hypotheses. You will produce publication-quality visualizations and reports, present findings clearly to cross-functional stakeholders, and championversion control,workflow managers, andreproducible research practices to strengthen code quality and method sharing across programs.

Finally, you will stay current with emerging tools inbioinformatics,AI/ML, andagentic AI, piloting new approaches, sharing learnings, and scaling successful methods across the portfolio.

Essential Skills and Experience

• You should have aPhD inBioinformatics,Computational Biology,Genomics,Molecular Biology,Computer Science, or a closely related quantitative discipline, with2-5 years of industry experience.
• Alternatively, you may have anMS in a relevant discipline with4-6years of industry experience in bioinformatics, computational biology, or genomics.
• A demonstrated track record of independent research throughpublications,conference presentations, or successful project delivery is expected.
• You should bring proficiency inRand/orPython for genomic data analysis, statistical computing, and data visualization, including tools such asggplot2,Bioconductor,tidyverse,pandas, andscikit-learn.
• Hands-on experience withNGS data analysis is required, including alignment tools such asSTAR,BWA, andBowtie2; quantification tools such asSalmon,featureCounts, andHTSeq; and variant calling tools such asGATK andbcftools.
• You should be familiar withRNA-seq analysis workflows, includingdifferential expression methods such asDESeq2,edgeR, andlimma, as well as pathway analysis and gene set enrichment approaches such asssGSEA andMSigDB. Experience working inLinux/Unix environments and withHPC job schedulers such asSLURM,SGE, orPBS, and/or cloud computing platforms such asAWS orGCP, is important.

You should also have working knowledge ofGit/GitHub and reproducible research practices, includingNextflow or similar workflow managers. A solid understanding ofmolecular biology fundamentals,genome annotation, and public bioinformatics databases such asNCBI,Ensembl,UniProt, andPDB is required, along with foundational knowledge ofmachine learning concepts and applied statistics relevant to biomarker discovery and genomic data.

Success in this role will also require strong analytical thinking, creative problem-solving, and the ability to translate complex datasets into actionable biological insights. You should have 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, orinflammatory disease -would be valuable.

We also welcome experience withcomparative genomics andmicrobial or viral genome analysis, includingpangenome methods,AMR gene detection, andphylogenetics.

Additional desirable experience includes buildingpredictive and prognostic models using supervised and unsupervised machine learning methods on clinical or preclinical omics data; familiarity withdeep learning frameworks such asPyTorch andTensorFlow; and exposure tobiological foundation models such asESM,EvolutionaryScale,scGPT,TranscriptFormer, andEvo.

We also value experience with or strong interest inagentic AI workflows for bioinformatics, includingLLM-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 asClaude Code orGitHub Copilot is a plus.

Exposure tosingle-cell RNA-seq tools such asSeurat,Scanpy, andCellRanger; knowledge ofstructural biology tools,protein modeling, orantigen/antibody design; and experience withcontainerization andinfrastructure-as-code would also be beneficial. Familiarity withLLM APIs and prompt engineering for scientific applications, including structured output generation and multi-agent system design, is also desirable.

Why AstraZeneca

AtAstraZeneca, 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 turndata,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.

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 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.

Date Posted

Closing Date

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.