Are you excited about extracting knowledge from totally novel, complex biological datasets? Do you believe that the complexity of the microbiome is an untapped source of new technologies? Want to be part of a company that’s unlocking biological complexity for good? If so, we want to meet you!
As our Lead Data Scientist, your contributions will be transformative: You will build Concerto’s data analysis platform from the ground up. The massive datasets we collect harbor tremendous potential, and, as our first data scientist and sixth member of our team, you will extract from these data the biological insights necessary to drive our discovery and development efforts. From the nitty-gritty details (e.g. hands-on data analysis and interpretation) to the 30,000-ft-view (e.g. working with the CEO and Chief Scientific Officer to plan data science growth at Concerto), you will tackle all aspects of starting a data science program at a new company. As you help Concerto grow, we’re excited to contribute to your intellectual and professional growth, and you’ll have the opportunity to advance with the company as we scale. As an early member of Concerto’s expanding team, you’ll play a critical role in developing Concerto’s culture and putting our core values into practice.
kChip is an ultra-high-throughput device that constructs and measures millions of defined microbial combinations (see links to publications below). kChip presents a completely new way of understanding the microbiome based on direct observation of microbial behavior. kChip data are microscopy images of millions of distinct microbial communities. You’ll use image analysis techniques to measure their optical features, and you’ll dig into these features to discover how community behavior is related to community size, composition, environment, etc. Your models will help engineer useful microbial communities from scratch.
- Design and implement an end-to-end proprietary kChip data analysis pipeline (microscopy images go in; knowledge comes out, including screening hits and statistical trends)
- Identify whether statistical trends in kChip data can be extrapolated or explained (e.g. can behavior of large combinations be predicted from small combinations?)
- Integrate kChip data with in vivo data to test our ability to predict in vivo function from kChip data
- Work with the Chief Scientific Officer and Head of Research to inform the design of kChip screens, as well as follow-up experiments, that will address working hypotheses generated from kChip data
- Design, implement, and maintain an organized data storage strategy
- Identify opportunities to extract new value from kChip data sets
- Embody Concerto’s values (see link below) in your work
- Bachelor’s degree with 5+ years of experience, or Masters/PhD with 3+ years of experience, in computational biology, computer science, data science, or related fields
- 3-5 years of experience designing and implementing data analysis methods, including image analysis, to gain knowledge from complex biological datasets
- Extensive experience implementing statistical inference, machine learning, and other analytical methods
- Human-friendly, reproducible coding habits (well-commented, version-controlled, etc)
- Strong written and verbal communication; an ability to communicate technical material to expert and non-expert audiences simply and clearly
- Demonstrated track record of working well in team environments
- Proactive, with a strong drive for problem solving and creative data exploration
- Startup experience
- Experience laying the foundation for scalable data management
- Experience growing and leading a data science team
- Microbiology or microbiome experience
- Kehe et al. PNAS 2019. https://www.pnas.org/content/116/26/12804
- Kehe et al. Biorxiv 2020. https://www.biorxiv.org/content/10.1101/2020.06.24.169474v1
- Our values: https://drive.google.com/file/d/1nfcHlZ8ohur9hCuKOnbFWxa8FlJT3l1P/view?usp=sharing
Applications: Please send your cover letter and resume or CV to Co-founder and CEO Dr. Cheri Ackerman at email@example.com.