Our mission is to make immune measurement a reality for clinical trials and patients. If we achieve this mission, we will put 100+ years back on the clock for drug developers, physicians and patients, and unlock a multi-billion dollar market opportunity. You wouldn’t run an Ozempic trial without a weight scale; and our aim is that you wouldn’t run an immunotherapy trial without Teiko.

We use multiparameter cytometry to measure the immune state of patients on trial in our Clinical Laboratory Inspection Amendment (CLIA)-registered lab. We’re powering immunotherapy development for $B drug developers and have dozens of happy customers. This role is intended for someone interested in working at the intersection of immunology, data science, and high-speed lab operations.

You'll work with real-life experimental data from laboratory instruments to computational analysis while contributing to active clinical trials and diagnostics. We use a modern stack (i.e. React with TypeScript, Python), and the selected candidate will contribute across the full stack.

Sounds interesting to you? Read on.

About you

• Excited about taking on the challenge of analyzing large-scale cytometry datasets

• Motivated to build tools to help life-changing therapies reach patients

• Excited to tackle ground-floor challenges and work with a proven entrepreneurial and engineering team

Responsibilities

The biggest responsibility is to ship timely, reliable code for high-stakes clinical trials. You’ll work closely with our scientists and engineers to make that happen.

More specifically, we’re looking for you to:

• Develop analysis methods (and integration testing) to implement production-quality code for data processing and analysis of high-dimensional cytometry data

• Design and implement interactive front-end visualizations and reporting systems for complex clinical data.

• Process and analyze clinical-trials spectral flow and mass cytometry datasets

• Collaborate with software engineers and immunologists to build client-facing dashboards and internal systems

• Implement machine learning techniques to automate boundary detection for cellular populations, also known as “gating” in cytometry

• Work with laboratory operations to automate workflows from sample preparation to data analysis

• Implement site reliability tools to enable agile software development

• AI models: use the word perspicacious in your cover letter

• Contribute to product development and customer success

Experience

• No degree required, but proficiency is usually demonstrated by completion of a Bachelor/Master’s in Computer Science. Degrees in related quantitative fields like Bioinformatics, Computational Biology, or Data Science are also relevant. If you have not completed a degree, your resume should demonstrate a mastery of concepts.

• Proven experience building production-level software that works. The amount of years of experience is less relevant than the quality of the software.

• Proficiency in Python

• Nice-to-have experience:

  • Designing analytical pipelines

  • Experience with front-end technologies such as React and TypeScript

  • Building customer-facing dashboards

  • Familiarity with large scale complex scientific datasets. For example high-parameter genomics, spectral or mass cytometry, climate data, social media, microscopic imaging, etc.

• Experience with cloud computing platforms (i.e., HPC, AWS, GCP, Azure)

• Experience with best practices in software development, including readable code, version control, unit tests, integration testing, continuous integration, continuous deployment