Director, Genomics & ctDNA Bioinformatics

AstraZeneca PLC
Location
Cambridge, Massachusetts
Job Type
Full-time
Posted
November 9, 2026
Salary Range
$182k - $272k USD

Job Description

AstraZeneca is committed to using genomics, data science, and artificial intelligence to accelerate scientific discovery and drug development.

Within Biomarker Sciences & Technologies, we are seeking an experienced computational scientist to lead bioinformatics strategy and analysis for minimally invasive and multimodal biomarkers, with particular emphasis on circulating tumor DNA (ctDNA), genomic data, and oncology applications.  This role will provide hands-on scientific and technical leadership across biomarker research and clinical development, developing and applying robust methods for genomic and ctDNA analysis, assay and pipeline benchmarking, data integration, and predictive and mechanistic modeling.

The successful candidate will translate complex molecular and clinical datasets into actionable evidence, establish fit-for-purpose analytical standards, and guide teams in the rigorous interpretation of biomarker results.  This position offers a unique opportunity to shape how computational genomics, ctDNA analytics, statistical modeling, and AI-enabled methods are used to answer complex translational questions and support biomarker-driven decisions across the oncology portfolio.

What You'll Do   Lead Genomics and ctDNA Bioinformatics  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 rigorous 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 that integrate genomic, ctDNA, clinical, and other biomarker data to generate actionable 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 clearly to multidisciplinary project teams and senior scientific stakeholders.  Drive AI Enablement and Innovation  Evaluate and implement machine learning and AI methods for genomic interpretation, ctDNA signal detection, multimodal data integration, and biomarker modeling.  Identify opportunities where advanced computational methods can improve analytical sensitivity, robustness, scalability, or biological insight.  Develop and promote scalable, reusable analytical tools, pipelines, and data products that enable consistent application 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.

Minimum

Qualifications: 7+ years of experience in bioinformatics, computational biology, genomics, biomarker analysis, or a related field.

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.    Desirable

AstraZeneca is committed to using genomics, data science, and artificial intelligence to accelerate scientific discovery and drug development.

Within Biomarker Sciences & Technologies, we are seeking an experienced computational scientist to lead bioinformatics strategy and analysis for minimally invasive and multimodal biomarkers, with particular emphasis on circulating tumor DNA (ctDNA), genomic data, and oncology applications.  This role will provide hands-on scientific and technical leadership across biomarker research and clinical development, developing and applying robust methods for genomic and ctDNA analysis, assay and pipeline benchmarking, data integration, and predictive and mechanistic modeling.

The successful candidate will translate complex molecular and clinical datasets into actionable evidence, establish fit-for-purpose analytical standards, and guide teams in the rigorous interpretation of biomarker results.  This position offers a unique opportunity to shape how computational genomics, ctDNA analytics, statistical modeling, and AI-enabled methods are used to answer complex translational questions and support biomarker-driven decisions across the oncology portfolio.

What You'll Do   Lead Genomics and ctDNA Bioinformatics  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 rigorous 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 that integrate genomic, ctDNA, clinical, and other biomarker data to generate actionable 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 clearly to multidisciplinary project teams and senior scientific stakeholders.  Drive AI Enablement and Innovation  Evaluate and implement machine learning and AI methods for genomic interpretation, ctDNA signal detection, multimodal data integration, and biomarker modeling.  Identify opportunities where advanced computational methods can improve analytical sensitivity, robustness, scalability, or biological insight.  Develop and promote scalable, reusable analytical tools, pipelines, and data products that enable consistent application 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.

Minimum

Qualifications: 7+ years of experience in bioinformatics, computational biology, genomics, biomarker analysis, or a related field.

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.    Desirable

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 that combine 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.    Why Join Us?  This role offers

the opportunity to help shape the future application of AI and advanced analytics within biomarker science.

You will work alongside leading experts across translational medicine, data science, and technology, contributing to innovative approaches that advance scientific understanding and support the development of life-changing medicines.  The annual base pay for this position ranges from $181,570.40 -$272,355.60 USD Annual.

Hourly and salaried non-exempt employees will also be paid overtime pay when working qualifying overtime hours. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.

In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program (salaried roles), to receive a retirement contribution (hourly roles), and commission payment eligibility (sales roles).

Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans. Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment.

If hired, employee will be in an “at-will position” and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

Date Posted 09-Nov-2026 Closing Date 15-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.

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Frequently Asked Questions

Where is this job located, and is it remote, hybrid, or on-site?
The role is based in Cambridge, Massachusetts, USA. The posting does not specify whether it is remote, hybrid, or on-site.
What qualifications and experience do I need?
You need a PhD in Bioinformatics, Computational Biology, Genomics, Statistics, Computer Science, Biomedical Engineering, or a related quantitative field, plus 7+ years of relevant experience. You also need deep NGS analysis experience, benchmarking and validation study design, Python and/or R proficiency, and scientific leadership skills.
What will I be responsible for in this role?
You will lead bioinformatics strategy and hands-on analysis for genomic and ctDNA biomarker studies and build reproducible workflows for QC, variant detection, and ctDNA quantification. You will also design benchmarking studies, build predictive models, and drive AI and machine learning methods. Communicating findings to multidisciplinary teams is part of the role.
What is the salary range?
Annual base pay ranges from $181,570.40 to $272,355.60 USD, depending on factors like location, skills, and experience. The role also offers a short-term incentive bonus opportunity and eligibility for the equity-based long-term incentive program for salaried roles.
What benefits are offered?
Benefits include a 401(k) retirement plan, paid vacation and holidays, and paid leaves. Health benefits include medical, prescription drug, dental, and vision coverage.
When is the application deadline?
The job was posted on 09-Nov-2026 and applications close on 15-Nov-2026. If you need a disability accommodation, complete the corresponding section in the application form.
Which team would I be part of?
The role sits within AstraZeneca's Biomarker Sciences & Technologies group, with a focus on oncology. You would work alongside experts across translational medicine, data science, and technology.

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Job Information

Source: builtin
AI Relevance: 96/100 (Highly relevant)
Remote Type: onsite
Skills & Tags:
boston biotech
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