We started Teiko Bio to use immune insights to help deliver life changing therapies to those who need them most. Today, Teiko delivers on its mission by supporting therapy development and informing clinical decision making. By using cutting edge mass cytometry, Teiko’s leading assay, the TokuProfile, maps characteristics of response, accelerates clinical pipeline candidates, and supports identification of novel discoveries.
- Familiar with single cell or genomics data analysis
- Motivated to help breakthrough therapies reach patients
- Excited to tackle ground-floor challenges and work with seasoned scientists and proven entrepreneurs
- Develop sample-to-answer workflow
- Develop and implement a centralized data management solution
- Build industrial, production-quality pipeline for data processing and analysis of high-dimensional cytometry data
- Design and implement visualizations and reports for high-dimensional cytometry data
- Develop and implement quality control automation
- Build production-quality client-facing web application
- Work with scientists to implement machine learning algorithms
- Contribute to product development and customer success
- No degree required, but proficiency usually demonstrated by getting a Bachelor/Master’s in computer science or computer engineering, or PhD in bioinformatics, computational biology, immunology, or related discipline. If you don’t have an advanced degree, your resume should demonstrate a mastery of concepts.
- Proficiency in commonly used languages: Python, R, etc.
- 3+ years’ experience in building production-level software
- Highly skilled in data management, including relational database
- Demonstrated experience with building customer-facing web applications
- Experience with cloud computing platforms (AWS, GCP, Azure)
- Experience with best practices in software development, including readable code, version control, unit tests, continuous integration
- Experience with Lab Information Management System (LIMS), such as Benchling (preferred but not required)
- Familiarity with large scale “omics” datasets: genomics, cytometry, etc.
- Demonstrated experience with the analysis of single-cell data
- Practical, working knowledge of modern bioinformatics tools