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Pfizer

Makes cancer drugs, vaccines and other medicines

Executive Director, Translational & Computational Biology - Translational & Computational Biology Team

Quantitative Biology & BiostatisticsPosted on Nov 10
Full-time$230.9k - $384.8k /yr

About the Job

Requirements

  • A PhD, MD, PharmD, or equivalent advanced degree in Computational Biology, Translational Biology, Bioinformatics, Genetics, Genomics, Systems Biology, Biomedical Sciences, Biostatistics, or a related discipline, with 10 or more years of relevant industry or research experience; alternatively, a Master's degree with 12 or more years of relevant experience, or an equivalent record of scientific and translational impact.
  • A sustained record of translating complex biological and clinical data into insights that influenced meaningful scientific, development, or portfolio decisions.
  • Experience leading cross-functional scientific or translational programs from an ambiguous question to an evidence-based decision.
  • Experience defining strategy and priorities for complex analytical, biomarker, precision-medicine, or data-driven work.
  • Experience applying computational and quantitative approaches to real-world biological and clinical questions.
  • Experience influencing senior stakeholders through clear scientific reasoning, evidence, and recommendations.
  • Experience operating with substantial autonomy in matrixed organizations and aligning contributors without relying on formal authority.
  • Working or strong proficiency in R and/or Python, or equivalent computational tools sufficient to work directly with data and analytical workflows.
  • Statistical reasoning, experimental design, and quantitative interpretation.
  • Biological and clinical data analysis and visualization.
  • Reproducible research and evidence-generation practices.
  • Knowledge of machine learning and artificial intelligence concepts relevant to biomedical research.
  • Ability to evaluate model outputs, uncertainty, limitations, and scientific validity.
  • Demonstrated depth in one or more major scientific domains such as multi-omics, single-cell or spatial biology, genetics and genomics, translational or systems biology, imaging or digital pathology, clinical development and biomarker science, or real-world data and evidence.
  • Deep intellectual curiosity and biological judgment.
  • Strategic thinking and the ability to identify the questions that matter most.
  • Scientific rigor, healthy skepticism, and evidence-based decision-making.
  • Comfort operating with ambiguity and high autonomy.
  • Ability to move fluidly between biology, data, artificial intelligence, and drug-development context.
  • Executive-level communication and influence across scientific and technical audiences.
  • A collaborative, low-ego approach to building trust and enabling others.
  • Permanent work authorization in the United States.

Responsibilities

  • Lead a portfolio of high-value biological, translational, and clinical questions across Research & Development.
  • Serve as a senior scientific bridge between therapeutic-area teams and the AI Core.
  • Shape analytical and artificial intelligence strategies, including study design, validation, and evidence standards.
  • Interpret complex multimodal evidence and translate it into clear scientific recommendations.
  • Influence scientific, development, and portfolio decisions through data and biological judgment.
  • Drive adoption and reuse of successful artificial intelligence-enabled scientific approaches across programs and teams.
  • Identify and prioritize questions where integrated biological, clinical, and computational evidence can materially change a scientific or development decision.
  • Lead scientific strategy from problem formulation through analysis, validation, interpretation, and recommendation.
  • Generate and test hypotheses that connect molecular mechanisms to patient biology, treatment response, and development strategy.
  • Ensure work is tied to measurable scientific, development, or portfolio outcomes.
  • Partner with AI scientists, engineers, computational biologists, statisticians, and domain experts to define fit-for-purpose approaches.
  • Define cohorts, endpoints, labels, biological annotations, evaluation criteria, and validation plans that reflect biological and clinical reality.
  • Guide selection and application of computational methods and artificial intelligence capabilities, including determining where new methods or models are required.
  • Challenge outputs for biological plausibility, robustness, generalizability, uncertainty, and decision relevance.
  • Serve as a trusted advisor to scientific and clinical leaders across discovery, translational medicine, and clinical development.
  • Bring emerging artificial intelligence capabilities into therapeutic-area workflows and help teams identify where they can create meaningful scientific advantage.
  • Build durable partnerships across Research & Development functions, connecting scientific needs, technical capabilities, and evidence.
  • Represent translational and computational perspectives in cross-functional program and portfolio discussions.
  • Lead or guide analyses involving multi-omics data, single-cell and spatial biology, genetics and genomics, perturbational and functional biology, imaging and digital pathology, clinical trial datasets, real-world data and evidence, scientific literature, internal knowledge, and other multimodal data sources.
  • Interpret results in biological, clinical, and development context.
  • Assess uncertainty, confounding, bias, alternative explanations, and failure modes.
  • Establish fit-for-purpose standards for rigor, reproducibility, validation, and evidence.
  • Distinguish statistically interesting findings from evidence that is actionable for Research & Development.
  • Communicate complex evidence clearly to scientific, clinical, technical, and senior leadership audiences.
  • Influence decisions in matrixed teams through scientific credibility, judgment, and execution.
  • Mentor and guide scientists and cross-functional colleagues, and elevate translational and computational fluency across teams.
  • Serve as an early adopter of artificial intelligence-enabled ways of working and help embed successful approaches into repeatable scientific practice.

Desired Qualifications

  • Significant experience in biotechnology or pharmaceutical Research & Development.
  • Demonstrated impact across drug discovery, translational research, clinical development, precision medicine, or biomarker strategy.
  • Experience applying or adopting artificial intelligence-enabled scientific workflows in real Research & Development settings.
  • Experience leading multidisciplinary teams or major cross-functional workstreams.
  • Deep expertise in one or more therapeutic areas and a track record of translating computational evidence into program or portfolio decisions.
  • Experience integrating multiple data types and working with artificial intelligence-enabled scientific workflows is strongly valued.

About the Company

Pfizer

Makes cancer drugs, vaccines and other medicines

Pfizer discovers, makes, and sells prescription medicines and vaccines for patients, doctors, and governments worldwide, with large businesses in vaccines, cancer, heart disease, and rare diseases. In 2020, its COVID-19 shot, developed with German partner BioNTech, became the first COVID-19 vaccine authorized in the United States. Its scientists find drug candidates and run clinical trials to prove they are safe and effective, and Pfizer then manufactures approved products in its own plants, earning most of its money from patented drugs before cheaper generic copies arrive. Pfizer was founded in 1849 as a chemicals business in Brooklyn and is based in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1849

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