About the job
At Teiko, our mission is to revolutionize immune measurement for clinical trials and patients alike. By achieving this goal, we aim to save drug developers, physicians, and patients over a century of time, while also unlocking a multi-billion dollar market opportunity. Just as a weight scale is essential for an Ozempic trial, we believe that a reliable immune measurement tool should be a standard for immunotherapy trials.
Utilizing advanced multiparameter cytometry techniques, we measure the immune status of patients participating in trials at our Clinical Laboratory Inspection Amendment (CLIA)-registered facility. As we support immunotherapy development for billion-dollar drug firms, we are proud to have numerous satisfied clients. This position is ideal for individuals eager to operate at the intersection of immunology, data science, and high-speed laboratory operations.
In this role, you will engage with real-world experimental data from laboratory instruments, conduct computational analyses, and contribute to ongoing clinical trials and diagnostics. Our modern tech stack includes React with TypeScript and Python, allowing you to work across the entire development spectrum.
If this excites you, we encourage you to explore further.
About You
Enthusiastic about analyzing large-scale cytometry datasets
Driven to create tools that facilitate life-altering therapies for patients
Eager to address foundational challenges while collaborating with a skilled entrepreneurial and engineering team
Responsibilities
Your primary responsibility will be to deliver timely, dependable code for high-stakes clinical trials, in close collaboration with our scientists and engineers.
Specifically, your tasks will include:
Developing analysis methodologies and integration tests to produce production-quality code for processing and analyzing high-dimensional cytometry data
Designing and implementing interactive front-end visualizations and reporting systems for complex clinical datasets
Processing and analyzing spectral flow and mass cytometry datasets from clinical trials
Collaborating with software engineers and immunologists to create client-facing dashboards and internal systems
Applying machine learning techniques to automate boundary detection for cellular populations, known as “gating” in cytometry
Partnering with laboratory operations to automate workflows from sample preparation through data analysis
