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AstraZeneca

Global pharmaceutical company developing prescription medicines

Director – Genomics & ctDNA Bioinformatics

Quantitative Biology & BiostatisticsPosted on Nov 9
Full-timeCambridge, MA, USAIn-person

About the Job

Requirements

  • At least 7 years of experience in bioinformatics, computational biology, genomics, biomarker analysis, or a related field.
  • A PhD in Bioinformatics, Computational Biology, Genomics, Statistics, Computer Science, Biomedical Engineering, or a related quantitative field.
  • Deep experience analyzing next-generation sequencing data and developing or applying bioinformatics workflows in biomedical research or drug development.
  • Demonstrated expertise in genomics, biomarker analysis, statistical modeling, data integration, and rigorous interpretation of complex molecular and clinical datasets.
  • Experience designing benchmarking or validation studies and evaluating analytical performance, including sensitivity, specificity, precision, reproducibility, and sources of bias.
  • Proficiency in Python and/or R and experience developing reproducible, version-controlled analytical workflows in a collaborative computing environment.
  • Ability to communicate complex technical concepts, analytical limitations, and decision-relevant conclusions to diverse scientific audiences.
  • Strong scientific leadership and collaboration skills, with experience working within multidisciplinary teams.

Responsibilities

  • Lead bioinformatics strategy and hands-on analysis for genomic and ctDNA biomarker studies across discovery, translational research, and clinical development.
  • Develop, evaluate, and apply reproducible workflows for sequencing quality control, variant detection, copy-number and other genomic analyses, ctDNA quantification, molecular response, and longitudinal disease monitoring.
  • Design benchmarking studies to compare assays, computational pipelines, calling thresholds, and analytical approaches using reference materials, orthogonal methods, tissue–plasma comparisons, and clinical datasets.
  • Build statistical, predictive, and mechanistic models integrating genomic, ctDNA, clinical, and other biomarker data to generate biological insights and support development decisions.
  • Define fit-for-purpose analysis plans, performance metrics, validation criteria, and standards for reproducibility, traceability, statistical rigor, and scientific interpretation.
  • Communicate analytical findings, assumptions, limitations, and recommendations to multidisciplinary project teams and senior scientific stakeholders.
  • Evaluate and implement machine learning and AI methods for genomic interpretation, ctDNA signal detection, multimodal data integration, and biomarker modeling.
  • Identify opportunities for advanced computational methods to improve analytical sensitivity, robustness, scalability, or biological insight.
  • Develop and promote scalable, reusable analytical tools, pipelines, and data products for consistent use across studies and programs.
  • Assess model performance, generalizability, bias, interpretability, and fitness for intended use, and ensure appropriate scientific and statistical validation.
  • Build organizational capability through technical leadership, code and methods review, education, and knowledge sharing.

Desired Qualifications

  • Direct experience with liquid biopsy and ctDNA analysis, including low-frequency variant detection, tumor fraction estimation, molecular response or progression, minimal residual disease, or longitudinal monitoring.
  • Experience benchmarking genomic assays or bioinformatics pipelines across platforms, vendors, sample types, or orthogonal technologies.
  • Knowledge of somatic variant calling, copy-number analysis, error suppression, sequencing quality metrics, assay limit-of-detection assessment, and tissue–plasma concordance analyses.
  • Experience developing predictive, longitudinal, or multimodal models combining genomic biomarkers with clinical, imaging, or other molecular data.
  • Experience applying machine learning or AI to biomedical data, with attention to model validation, interpretability, generalizability, and bias.
  • Knowledge of oncology biomarker development, translational science, precision medicine, and clinical development.

About the Company

AstraZeneca

Global pharmaceutical company developing prescription medicines

AstraZeneca develops and markets prescription medicines and vaccines worldwide, with a focus on oncology, cardiovascular/metabolic, respiratory, and infectious diseases. Its products work by targeting specific biological pathways or cells, using small-molecule therapies, biologics, and vaccines to treat diseases or prevent infections. It differentiates itself through its dual heritage from Sweden and the UK, a broad pipeline, and strong R&D and collaborations that move from discovery to patient access. Its goal is to improve people’s health by discovering, developing, and delivering medicines and vaccines to patients worldwide.

Company size
10,001+
Company stage
IPO
Headquarters
Cambridge, United Kingdom
Founded
1913

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