Scientist, Data Science

AstraZeneca plc
Waltham, MA, United States
5 days ago
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Role details

Contract type
Internship / Graduate position
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
0 years minimum
Compensation
$118,870.0 - $178,306.0
Working hours
Regular working hours

Tech stack

Data Analysis Bioinformatics Clinical Data Repository Computational Biology Computer Programming Databases Data Integration Data Visualization Github Python (Programming Language) Machine Learning Random Forest
+1 more
Xgboost

Job description

  • 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.

Requirements

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., * 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., * 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.

Benefits & conditions

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.

About the company

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

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