Jobs / United States / Astrazeneca Pharmaceuticals Lp
Senior Scientist, Bioinformatics / Computational Biology
Astrazeneca Pharmaceuticals Lp · 🇺🇸 US - Cambridge - MA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 99 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Astrazeneca Pharmaceuticals Lp paid sponsored hires in similar roles3 certified filings for “Senior Scientist, High-Throughput Experimentation (HTE)” (Biochemists and Biophysicists) in MA: $139k–$142k, median $141k. Most were filed at wage level II (67%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Astrazeneca Pharmaceuticals Lp
The US Department of Labor certified 99 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Astrazeneca Pharmaceuticals Lp →
About the role
Are you ready to harness multi-omics , comparative genomics , and agentic 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 shape antigen design , patient stratification , and translational strategy across high-priority programs. Based in Cambridge , MA you will work in a collaborative, multidisciplinary environment alongside immunologists , molecular biologists , and data scientists . If you thrive at the intersection of computation and experiment—designing reproducible pipelines on HPC and cloud platforms while partnering closely with the lab to iterate rapidly—this role offers the opportunity to influence study design, guide go/no-go decisions , and help advance novel immune-based therapies toward patients. Accountabilities • You will design, implement, and deliver robust analyses across genomics , bulk and single-cell transcriptomics , and multi-omics to answer program-critical questions with statistical rigor. You will assemble genomes, call variants, and perform comparative genomics and phylogenetic analyses on bacterial and viral pathogens to inform antigen selection and surveillance strategy. • You will 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. You will also build, optimize, and maintain reproducible workflows using HPC schedulers and AWS to scale analyses, reduce turnaround time, and ensure traceability. In addition, you will design and integrate LLM-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 through differential expression , pathway enrichment , and functional 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 champion version control , workflow managers , and reproducible research practices to strengthen code quality and method sharing across programs. Finally, you will 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 • You should have a PhD in Bioinformatics , Computational Biology , Genomics , Molecular Biology , Computer Science , or a closely related quantitative discipline, with 2 –5 years of industry experience . • Alternatively, you may have 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 is expected. • You should bring 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 is required, including alignment tools such as STAR , BWA , and Bowtie2 ; quantification tools such as Salmon , featureCounts , and