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Senior Translational and Computational Biologist

Pfizer
United States - Washington – Bothell; United States - California - San Diego; United States - Massachusetts - Cambridge; United States - Connecticut - Groton +2 more Posted Nov 6, 2026
Full-time

About this role

Launch Your Career at the Intersection of Biology, AI, and Drug Discovery

At Pfizer, breakthroughs in biology, data science, and artificial intelligence are changing how medicines are discovered and developed.

As a Senior Translational and Computational Biologist, you'll help transform complex biological and clinical data into insights that support critical scientific decisions across research and development.

This is an opportunity for computational and translational scientists who want to combine deep biological understanding with data, computational approaches, and emerging AI capabilities to influence real drug discovery and development programs.

You'll work alongside experienced computational biologists, AI scientists, translational researchers, clinicians, and therapeutic area experts while contributing to scientific questions that have the potential to improve patients' lives around the world.

Why This Role Is Different

Build Expertise While Doing Meaningful Work

This role is designed for scientists ready to take ownership of important biological and translational problems while expanding their ability to apply computational and AI-enabled approaches.

You'll independently lead defined analyses, biological investigations, and use-case components while receiving guidance, mentorship, and exposure to some of the most challenging scientific questions in healthcare.

Learn How Science Drives Decisions

You'll help support research across areas such as:

  • Target identification and validation
  • Biomarker discovery
  • Patient stratification
  • Disease biology
  • Translational research
  • Clinical development
  • Business development assessments

Most importantly, you'll learn how computational insights influence decisions throughout the drug development lifecycle.

Grow Beyond Data Analysis

Computational biologists at Pfizer are not downstream analysts waiting for completed models.

They help shape questions, interpret evidence, challenge assumptions, and translate data into scientific understanding. This role provides an opportunity to develop those capabilities over time while building confidence and credibility as a scientific partner.

Develop Domain and Customer Fluency

You'll gain firsthand experience working with biological, translational, clinical, and therapeutic-area stakeholders while learning how to translate scientific needs into analytical approaches and actionable insights.

Bridge AI, Data, and Biology to Drive R&D Impact

This role sits at the intersection of the AI Core and Pfizer's scientific and therapeutic-area organizations. You may come from a computational or translational biology background; what matters most is deep biological and scientific judgment combined with the ability to use data, computational approaches, and emerging AI capabilities to answer important questions.

You will work closely with discovery, translational, clinical development, and other R&D teams to identify high-value problems, connect them with the right AI and analytical capabilities, interpret results in biological and clinical context, and help translate new approaches into scientific practice. You will be an early adopter of new AI-enabled ways of working and a trusted scientific partner who helps therapeutic-area teams use these capabilities effectively.

The Opportunity

As a Senior Translational and Computational Biologist, you will apply computational and biological expertise to help answer high-value scientific questions using diverse biological, molecular, and clinical datasets.

This is a role where success is measured not by leading large scientific programs, but by consistently delivering high-quality analyses, building domain expertise, and developing scientific judgment.

You will:

  • Own scoped analyses and defined biological investigations with appropriate guidance
  • Partner with scientists to understand biological questions and analytical needs
  • Apply computational methods to generate high-quality scientific insights
  • Build expertise in disease biology, drug discovery, and development
  • Learn how computational evidence supports scientific and portfolio decisions
  • Develop increasing independence in scientific problem-solving and stakeholder engagement

This role is ideal for individuals who enjoy learning, thrive in collaborative environments, and want to build a long-term career at the intersection of computation, biology, and medicine.

What You'll Do

  • Conduct High-Impact Biological Analyses

  • Independently execute defined analyses across biological, molecular, genetic, clinical, and translational datasets

  • Investigate scientific questions and summarize findings with clarity and rigor

  • Generate hypotheses and identify meaningful biological patterns

  • Deliver evidence-based insights that support scientific decision-making

  • Translate Scientific Questions into Analytical Approaches

  • Work with experienced computational biologists and scientific partners to understand research challenges

  • Help define study populations, cohorts, labels, biological annotations, and evaluation criteria

  • Translate biological questions into executable computational workflows

  • Learn how analytical choices influence scientific outcomes

  • Develop Domain Expertise

  • Build understanding of disease biology, clinical development, and drug discovery processes

  • Learn how therapeutic area teams approach scientific decision-making

  • Develop familiarity with customer and stakeholder needs

  • Become a trusted contributor within defined scientific domains

  • Work Across Diverse Scientific Data Types

You may contribute to analyses involving:

  • Multi-omics data

  • Single-cell biology

  • Spatial biology

  • Genetics and genomics

  • Imaging data

  • Perturbational biology

  • Clinical trial datasets

  • Real-world data and evidence

  • You'll have opportunities to deepen expertise in one domain while becoming increasingly comfortable working across multiple data modalities.

  • Build Scientific and Analytical Judgment

  • Interpret results in biological and clinical context

  • Assess uncertainty, limitations, and alternative explanations

  • Apply statistical and computational best practices

  • Strengthen reproducible research practices and documentation standards

  • Grow as a Scientific Partner

  • Communicate findings clearly to scientific stakeholders

  • Participate in multidisciplinary project discussions

  • Learn how to influence decisions through evidence

  • Build the scientific credibility and stakeholder fluency needed to take on increasingly complex work

  • What You Bring

  • Education & Scientific Foundation

You have:

  • A PhD preferred in Computational Biology, Bioinformatics, Genetics, Genomics, Systems Biology, Biostatistics, Biomedical Engineering, or a related scientific discipline

  • A Master's degree with 2+ years of relevant experience

  • Most importantly, you have demonstrated success applying computational approaches to biological or biomedical problems and a strong desire to continue learning

  • Demonstrated Analytical Ownership

You have experience:

  • Independently conducting scientific or biological analyses

  • Managing defined projects or analytical workstreams

  • Applying computational methods to real-world scientific questions

  • Delivering clear, data-driven conclusions and recommendations

  • Working effectively with limited oversight while seeking guidance when needed

  • We are looking for computational biologists who have demonstrated the ability to own their work, deliver quality analyses, and continuously expand their expertise.

  • Technical Proficiency

You bring working or strong proficiency in:

  • R and/or Python (or equivalent computational tools)

  • Statistical analysis

  • Data visualization

  • Reproducible research practices

  • Biological data analysis

  • Machine learning fundamentals You have demonstrated experience in at least one major scientific data domain such as:

  • Multi-omics

  • Single-cell biology

  • Spatial biology

  • Genetics and genomics

  • Imaging

  • Clinical data

  • Real-world data

  • Experience integrating multiple data sources is a plus, but not required.

  • Learning Agility & Scientific Mindset

Successful candidates demonstrate:

  • Strong intellectual curiosity

  • Analytical rigor

  • Attention to detail

  • A growth mindset

  • Willingness to learn new biological domains

  • Ability to incorporate feedback

  • Enthusiasm for partnering with scientists and stakeholders

  • We're looking for people who are just as excited about learning as they are about applying what they already know.

  • Preferred Qualifications

  • Experience in biotechnology, pharmaceuticals, healthcare, or biomedical research

  • Experience supporting drug discovery or development activities

  • Familiarity with AI-enabled scientific workflows

  • Experience working on multidisciplinary scientific teams

  • Exposure to translational, clinical, or therapeutic-area research

  • Why Pfizer

  • At Pfizer, computational biology is becoming an increasingly important driver of scientific discovery.

  • You'll have the opportunity to work on meaningful scientific problems, collaborate with exceptional colleagues, and see how your analyses contribute to research decisions that can ultimately improve patient outcomes.

Here, you'll find:

  • Meaningful scientific ownership from day one

  • Opportunities to build deep biological expertise

  • Exposure to cutting-edge AI, data science, and biomedical research

  • World-class mentors and collaborators

  • Clear opportunities for growth and development

  • The chance to help accelerate discoveries that matter

  • If you're looking for a place where you can apply your computational skills, deepen your scientific expertise, and grow into a highly impactful computational biologist, Pfizer offers an exceptional opportunity to build your career.

  • Work

Location

Assignment

Hybrid: Colleagues must live within commuting distance of a Pfizer location and work on-site an average of 2.5 days per week.

The annual base salary for this position ranges from $106,000.00 to $176,600.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 15.0% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.

This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview.

Relocation assistance may be available based on business needs and/or eligibility.

Candidates must be authorized to be employed in the U.S. by any employer.

U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.

Sunshine Act

Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimburs

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