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Cancer Computational Biologist

Zephyr AI

Zephyr AI

Posted on Thursday, March 14, 2024


Zephyr is building an innovative AI platform to improve the way cancer, diabetes, and other chronic diseases are treated. Zephyr aggregates massive, diverse data sets and harnesses advanced technologies and AI to uncover actionable insights that will empower healthcare providers to deliver more effective, personalized care, and realize cost savings throughout the healthcare system. Zephyr is based in Tysons Corner, VA, and currently operates as a remote-first organization.



We seek a highly skilled research scientist with expertise in cancer, systems biology, and computational biology to join our growing multidisciplinary team working to advance precision oncology. The ideal candidate will work independently and in collaboration with other research team members to apply their skills to devise machine learning approaches to extract non-obvious insights from large biomedical datasets. The successful candidate will also be responsible for analyzing large-scale multi-omics data, mining publicly available data sources, and designing experiments to validate model predictions. This role requires communicating computational results and outcomes to a multidisciplinary team of scientists, data scientists, external collaborators, and partners. In addition, you will be working collaboratively with members from the data science, bioinformatics, and engineering teams.


We are a growing multi-disciplinary team delivering innovative precision medicine solutions to cancer patients. Our Research team analyzes a wide range of multi-omics and multi-functional data from publicly available databases and Real World Data providers. We use this data to develop predictive models that enhance our understanding of cancer and guide product development based on these insights. We are excited to share our passion for applying innovative machine learning techniques to save patients' lives with you and for your perspective to help shape our team's goals.


  • Lead analysis and interpretation of molecular (such as WES/WGS, RNA-Seq) and functional (such as pharmacological and CRISPR screens) datasets and clinical RWE cohorts.

  • Design, implement, and document algorithms and pipelines, ensuring their alignment with the objectives of ongoing and future projects aimed at unraveling the complexities of cancer genomics.

  • Formulate research hypotheses and develop computational methods to enhance biological interpretation of predictive models.

  • Build initial prototypes of predictive models in the space of cancer biology, drug response, and patient outcome prediction.

  • Lead discussion and present your analysis to members within and outside of the research science team. You may also communicate your work to the broader scientific community through presentations at scientific conferences (such as AACR, ASCO etc.), peer-reviewed publications and public seminars.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.


  • PhD in computational biology, genomics, cancer biology or related discipline.

  • Extensive experience with analyzing and interpreting omics (WES/WGS, DNA methylation, RNA-Seq, etc.), and high-throughput screen (pharmacological screens, and CRISPR perturbation assays) data.

  • Strong knowledge of Python/R and common data analysis packages (e.g., pandas, numpy, scikit-learn etc.)

  • Experience with analyzing and interpreting pathways and biological networks. Demonstrated ability to generate biological insights from omics data, through peer-reviewed publications or relevant work products.

  • Track record of completed scientific projects as evidenced by publications and preprints

  • Familiarity with drug screening databases (CTRP, GDSC, PRISM) and publicly available cancer datasets (CCLE, DepMap, TCGA, AACR Project GENIE, etc.)

  • Deep understanding of biostatistics and data analysis tools.

  • A critical mindset for data integrity, quality assurance, and documentation.

You will be a step ahead if you have:

  • Experience working in a version control environment (such as github).

  • Excellent written and oral communication skills necessary to explain complex data and analysis findings to non-experts.

  • Familiarity with pharmaceutical or biotech industry and meeting regulatory requirements.

  • Experience working in a fast-paced startup environment.


This is a full-time exempt position reporting to the Principal Computational Biologist. This position requires the ability to work cross functionally within the organization.

We offer competitive compensation as well as a comprehensive benefits package including:

  • United Healthcare PPO, HMO, and HDHP plans > 100% company paid for you + family

  • Dental (including orthodontic coverage) > 4 carriers, 100% company paid for you + family

  • Vision > 2 carriers, 100% company paid for you + family

  • Health Savings Account ( HSA) + Flexible Spending Account (FSA)

  • Basic Life and AD&D Insurance > 100% company paid

  • Voluntary benefits: short term and long term disability, supplemental AD&D, supplemental life, pet insurance

  • Paid maternity and paternity leave

  • Unlimited paid time off

  • 15 Paid holidays

  • 401(k) program

  • Work from home + cell phone/internet reimbursement

  • Unlimited 1:1 tax advisory sessions with our equity management team

  • Employee referral bonus

  • Employee assistance program (EAP)

  • Opportunities for advancement

We are an equal opportunity employer

Zephyr AI provides equal employment opportunities (EEO) to all applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. Zephyr AI complies with applicable state and local laws governing non-discrimination in employment in every location in which the company operates. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.