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 test, the TokuProfile, maps characteristics of response, accelerates clinical pipeline candidates, and supports identification of novel discoveries.

About you:

• Expert in 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

Responsibilities:

• Leading a team of computational biologists to develop systems and processes to analyze high-dimensional immune [i.e. mass cytometry] datasets
• Developing and implementing the data analysis strategy for

• biomarker discovery studies, particularly in the immunotherapy space
• internal R&D activities
• increasing report generation efficiency for customer data

• Delivering high-performance customer-facing releases and improvements
• Developing customer-facing platforms for data visualization and reporting
• Explaining results to customers and answering key questions 
• Identifying key areas of needs for the team and staffing appropriately

Experience:

• Experience in:

• leading computational teams to answer biological questions
• the analysis of single-cell data, preferably mass or flow cytometry
• working with clinical data, particularly in the oncology space
• working with clinical samples, preferably in a diagnostic setting
• delivering timely, high-quality results to customers

• No degree required, but completing an advanced degree in biology, bioinformatics, immunology or related discipline is one way to demonstrate proficiency in our field
• Proficiency in commonly-used data science languages: Python, R, etc.
• Familiarity with cloud computing platforms, preferably AWS
• Practical, working knowledge of modern bioinformatics tools
• Familiarity with large scale, high-throughput “omics” datasets: cytometry, genomics, etc.

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