AstraZeneca

AstraZeneca

Posted via Workday

Senior Scientist, Data Science

Apply by Nov 4, 2026

Posted Oct 29, 2026

Role at a glance

Job function
AI & Data Data Science
Salary
$118.9K – $178.3K/yr
Location
Waltham, Massachusetts, United States
Employment
Full-time
Experience
Senior Level Minimum 2 years of experience working with large patient-derived ‘omics datasets and clinical data to identify disease-associated pathways, candidate therapeutic targets, and biomarkers.
Education
Ph.D. in Bioinformatics, Computational Biology, Data Science, Epidemiology, or a related field (0–2 years post-graduate experience).

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Role Summary

AI-generated

This Senior Scientist role in data science sits within a newly formed early oncology R&D team and focuses on mining large datasets for target identification, mechanism of action studies, and biomarker strategy development, with particular attention to immune system function and aging. The role works alongside wet-lab scientists and contributes data-driven insights to the project team.

What You'll Do

  • Process and analyze large-scale biobank datasets, human population data, and in-vitro biological data using established analysis pipelines
  • Apply analytical methods and machine learning algorithms to help identify potential therapeutic targets and biomarkers
  • Partner with wet-lab scientists to analyze experimental results for target identification and mechanism of action studies
  • Generate high-quality visualizations and reports to communicate findings to the project team
  • Provide computational insights that contribute to the development of biomarker strategies
  • Actively participate in team meetings, presenting data-driven insights to help the group meet project milestones

Generated from the employer's posting. Verify important details before applying.

View full posting

Qualifications

A PhD in a computational or data science field with at least 2 years of experience analyzing large omics and clinical datasets, plus proteomics, NGS, and programming skills.

Required

  • Ph.D. in Bioinformatics, Computational Biology, Data Science, Epidemiology, or a related field (0–2 years post-graduate experience)
  • Minimum 2 years of experience working with large patient-derived ‘omics datasets and clinical data to identify disease-associated...
  • Minimum 2 years of experience developing reproducible pipelines for proteomics preprocessing, QC, harmonization, and performing...
  • Working experience designing and analyzing CRISPRi perturbation studies, integrating splicing, transcriptomic, and proteomic evidence to...
  • Strong proficiency in Python or R
  • Solid understanding of statistical analysis and foundational machine learning techniques
  • Hands-on experience with NGS data analysis (e.g., RNA-seq, DNA methylation, ChIP-seq, or ATAC-seq)
  • Experience with, or a strong desire to learn, proteomic data analysis and multi-omic data integration

Preferred

  • Prior experience or familiarity with biomarkers of immune system aging/function
  • Prior experience or internship in the pharmaceutical or biotechnology industry
  • Prior experience running large-scale association testing (e.g., genome-wide association studies [GWAS], epigenome-wide association...
  • Familiarity with methods in statistical genetics (e.g., Mendelian randomization, fine-mapping, colocalization)
  • Familiarity with machine learning analysis architectures (e.g., random forest, gradient boosting, transformers)
  • Familiarity with public biological databases (e.g., GTEx, TCGA), epidemiological cohort data (e.g., TOPMed cohorts), or biobanks (e.g.,...
  • Familiarity or prior experience with agentic AI in the context of analysis code pipeline development and biological analysis
  • Evidence of scientific contribution through publications, posters, or GitHub repositories

Original job description

Content provided by the employer

We are seeking a highly motivated Senior Scientist to join a newly formed, dynamic team within early oncology R&D. The successful candidate will leverage their data science expertise in mining large datasets to drive our efforts in target identification, mechanism of action (MOA) studies, and biomarker strategy development, with a particular focus on analyses related to the function and aging of the immune system. At AstraZeneca, you'll have the opportunity to make a significant impact on the future of healthcare while working in a collaborative environment at the cutting edge of research. The ideal candidate will thrive in this setting, contributing to our growth trajectory as we build our evolving team.

 

Key Responsibilities:

  • Execute and Maintain Pipelines: Process and analyze large-scale biobank datasets, human population data, and in-vitro biological data using established analysis pipelines.
  • Analytical Support: Apply analytical methods and machine learning algorithms to help identify potential therapeutic targets and biomarkers.
  • Cross-Functional Collaboration: Partner with wet-lab scientists to analyze experimental results for target identification and Mechanism of Action (MOA) studies.
  • Data Visualization: Generate high-quality visualizations and reports to communicate findings to the project team.
  • Strategic Contribution: Provide high-quality data and computational insights that contribute to the development of biomarker strategies.
  • Team Participation: Actively participate in team meetings, presenting data-driven insights to help the group meet project milestones.
  • Continuous Learning: Stay current with the latest developments in data science and bioinformatics tools.

Qualifications:

  • Education: Ph.D. in Bioinformatics, Computational Biology, Data Science, Epidemiology, or a related field (0–2 years post-graduate experience).
  • Data Experience: Minimum 2 years of experience working with large patient-derived ‘omics datasets and clinical data to identify disease-associated pathways, candidate therapeutic targets, and biomarkers.
  • Proteomics Experience: Minimum 2 years of experience developing reproducible pipelines for proteomics preprocessing, QC, harmonization, and performing proteome-wide association studies.
  • Perturbation Analysis Experience: Working experience designing and analyzing CRISPRi perturbation studies, integrating splicing, transcriptomic, and proteomic evidence to resolve molecular mechanisms.
  • Coding Proficiency: Strong proficiency in Python or R.
  • Technical Knowledge: Solid understanding of statistical analysis and foundational machine learning techniques.
  • Genomics Foundation: Hands-on experience with NGS data analysis (e.g., RNA-seq, DNA methylation, ChIP-seq, or ATAC-seq).
  • Multi-omics Interest: Experience with, or a strong desire to learn, proteomic data analysis and multi-omic data integration.
  • Operational Skills: Excellent problem-solving skills, attention to detail, and the ability to manage multiple tasks in a fast-paced environment.
  • Communication: Ability to clearly present data and technical workflows to a multidisciplinary team.

Desired Skills and Attributes:

  • Prior experience or familiarity with biomarkers of immune system aging/function.
  • Prior experience or internship in the pharmaceutical or biotechnology industry.
  • Prior experience running large-scale association testing (e.g., genome-wide association studies [GWAS], epigenome-wide association studies [EWAS], proteome-wide association studies).
  • Familiarity with methods in statistical genetics (e.g., Mendelian randomization, fine-mapping, colocalization).
  • Familiarity with machine learning analysis architectures (e.g., random forest, gradient boosting, transformers).
  • Familiarity with public biological databases (e.g., GTEx, TCGA), epidemiological cohort data (e.g., TOPMed cohorts), or biobanks (e.g., UK Biobank, FinnGen).
  • Familiarity or prior experience with agentic AI in the context of analysis code pipeline development and biological analysis.
  • Evidence of scientific contribution through publications, posters, or GitHub repositories.

As AstraZeneca continues to put patients at the forefront of our mission, we are excited for our move to Kendall Square/Cambridge in 2026. Find out more information here: Kendall Square Press Release


Ready to join us on this mission? Apply now!


Competitive remuneration and benefits apply

We offer a competitive Total Reward program including a market driven base salary, bonus and long-term incentive. We have a generous paid time off program and a comprehensive benefits package.


The annual base pay for this position ranges from $118,870.40 - $178,305.60. 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

28-Oct-2026

Closing Date

03-Nov-2026

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.

AstraZeneca

About the company

AstraZeneca

Large Enterprise

AstraZeneca is a global biopharmaceutical company dedicated to the research, development, and commercialization of innovative medicines. Headquartered in Cambridge, UK, the company focuses on areas such as oncology, cardiovascular, renal, metabolism, and respiratory diseases, striving to deliver life-changing treatments to patients. With a strong commitment to scientific excellence and collaboration, AstraZeneca invests in cutting-edge technologies and partnerships to drive advancements in healthcare. The company is also committed to sustainability and corporate responsibility, aiming to make a positive impact on communities worldwide.