Senior Scientist, Bioinformatics

AstraZeneca combines cutting-edge science, data, and artificial intelligence to transform how we discover and develop medicines. As part of Data Sciences and Quantitative Biology (QuBi), this role collaborates with chemical biology and proteomics scientists supporting therapeutic areas across AstraZeneca. Based in Cambridge, Massachusetts, you will work at the intersection of mass spectrometry-based (MS) proteomics and computational biology, building the data platform and analytical foundations for high-throughput proteomics and emerging molecular assays.

Responsibilities

• Workflow development and automation
  • Design, implement, and maintain end-to-end MS-based proteomics analysis pipelines (DDA and DIA; label-free, TMT/iTRAQ, SILAC) for processing, analysis, interpretation, and visualization of high-throughput proteomics data.
  • Wrap and orchestrate tools into portable, versioned workflows using Nextflow or Snakemake.
  • Develop tools and workflows with interfaces, metadata, and execution standards to support reuse by emerging agentic and AI-enabled systems.
  • Containerize tool environments (Docker, Kubernetes) and deploy pipelines to HPC (Slurm) and/or cloud compute.
  • Establish software engineering practices for the group—version control, code review, unit and regression testing, CI/CD, documentation, and release management.
• Data management and infrastructure
  • Design and maintain a proteomics data model and storage strategy for raw files, intermediate results, processed matrices, and analysis provenance.
  • Apply FAIR principles and appropriate data governance, access control, and retention policies in collaboration with IT/security.
  • Build searchable result databases (using Snowflake/PostgreSQL) and interfaces (using R Shiny or Streamlit).
• Analysis and scientific collaboration
  • Perform proteomics analyses integrating chemical biology and experimental metadata to generate biological insight.
  • Apply domain expertise in MS-based proteomics to support study design, data interpretation, quality assessment, and biological insight generation, particularly in chemical biology applications.
  • Contribute to the development of scalable analytical methods and digital capabilities, including AI-enabled and agentic approaches, to support scientific discovery and decision-making.

Requirements

• PhD in bioinformatics, computational biology, proteomics, biostatistics, data science, computer science, or a related discipline, or equivalent research experience.
• Solid grounding in the statistics of high-dimensional omics data.
• Demonstrated experience in bioinformatics and data analysis, with the ability to develop and apply reproducible analytical workflows for complex biological datasets.
• Experience with cloud platforms (such as AWS or Azure), covering core concepts like virtual machines, storage buckets, and basic cloud networking.
• Experience designing scalable omics data models and applying FAIR data principles and data governance.
• Experience with programming and data analysis in languages such as R and/or Python, and familiarity with scientific software development best practices.
• Experience building reproducible workflows with a pipeline framework (Nextflow, Snakemake) and containers in a Linux environment.
• Proficiency with version control (Git/GitHub) and collaborative software development practices.
• Ability to work as an independent scientific contributor while collaborating effectively across multidisciplinary teams.
• Strong communication skills, with the ability to explain complex scientific and technical concepts to diverse audiences and support adoption of analytical solutions.

Preferred Qualifications

• Demonstrated experience analyzing MS-based discovery proteomics data, with practical command of at least one major search/quantification platform (FragPipe, DIA-NN, Spectronaut, Proteome Discoverer, or equivalent).
• Experience developing or applying machine learning and AI for scientific data analysis, interpretation, or workflow automation.
• Experience in multi-omics analysis is a plus.
• A track record of scientific innovation demonstrated through publications, conference presentations, open-source contributions, software products, or deployed analytical tools in bioinformatics, AI, or data science.

Benefits

• Annual base salary range: $116,284.00 to $174,426.00, with variations based on market location, job-related knowledge, skills, and experience.
• Short-term incentive bonus opportunity.
• Eligibility to participate in equity-based long-term incentive program (salaried roles) or retirement contribution (hourly roles).
• Qualified retirement program (401(k) plan).
• Paid vacation and holidays; paid leaves.
• Health benefits including medical, prescription drug, dental, and vision coverage.