Full Time | San Francisco Bay Area


Send your resume and a short introduction to:

Loyal is an early stage company developing drugs to help dogs live longer, healthier lives. We see aging as a disease that is able to be slowed and improved with medicines. Loyal was spun out of Laura Deming’s The Longevity Fund and is well funded by top venture capitalists and angels.

We are hiring a Biostatistician to join our growing Computational Biology team! This is a great opportunity for a biologist with a strong statistical background to make the jump into the computational world, or a recent statistics graduate with biological leanings to use their powers to help push forward longevity research. You will work closely with our scientists and regulatory personnel to analyze and interpret experimental results and create reports to be submitted to the FDA. In addition you will support regulatory experimental designs by performing statistical modeling and power calculations. Being a startup, there will be many opportunities to strongly contribute to projects outside of your core competency.

Loyal is founded and led by a first-gen, female CEO – we encourage and look forward to diverse applicants.

As part of the Computational Biology team you will:

  • Support ongoing lab and clinical experiments through statistical analyses

  • Support the design of experiments through modeling and power calculations

  • Create and contribute to documentation that is sent to regulatory agencies

  • Build best practices documentation to catalog any learnings from interactions with regulatory agencies

  • Identify opportunities both internally and externally that you or the team can provide value to

  • Assist in endpoint development through research into assays and modeling outcomes

Basic Qualifications

  • BA/BS in Statistics, Mathematics, or other relevant field

  • 1-5 years of relevant experience, course projects count

  • Demonstrated statistical knowledge through coursework, repositories, publications or writings

  • Programming experience (Matlab, Python, R)

Preferred Qualifications

  • PhD in a statistically intensive field (biology, psychology, etc) or prior industry work in statistical modeling in a regulatory environment

  • Demonstrated experience in experimental design and post hoc statistical analysis

  • Demonstrated experience writing documentation for regulatory submissions

  • Fluency in python and use of Jupyter Notebooks

  • Strong writing and communication skills

How you work and think

  • Strong desire to work collaboratively within a team and across teams

  • Always looking for opportunities to assist others

  • Desire to learn and grow in ability and responsibilities

  • Process driven - creates frameworks to tackle challenging problems

  • Mission driven - able to put day to day work in the context of the overall goals of the company

  • Track record of communicating with technical and non-technical stakeholders

  • Able to work in a fast paced and ever-changing environment

  • Empathy to others and low ego

Interested? Email