Scientist/Sr. Scientist, Computational Biology

Kaleido Biosciences – Lexington, MA

Scientist/Sr. Scientist, Computational Biology


Kaleido Biosciences is a clinical-stage healthcare company with a differentiated, chemistry-driven approach to leveraging the potential of the microbiome organ to treat disease and improve human health. The Companys Microbiome Metabolic Therapies (MMT) are designed to modulate the metabolic output and profile of the microbiome by driving the function and distribution of the organs existing microbes. Kaleido is advancing a broad pipeline of MMT candidates to address a variety of diseases and conditions with significant unmet patient needs. The Companys human-centric discovery and development offers the potential to be faster and more cost-efficient than traditional drug development. We also have an exceptional team that is committed to scientific innovation, transforming lives and building a strong culture.


Kaleido Biosciences is seeking an exceptional, highly motivated Scientist/Senior Scientist to play a key role in the companys effort to bring current and future MMTs to patients and improve human health. This individual will join dynamic, highly collaborative and interdisciplinary teams that span all stages of the drug discovery process, from discovery to clinical trials. Our teams combine significant drug discovery experience with leading edge knowledge of microbiome biology. The position requires building strong cross-functional relationships throughout the organization. The successful candidate will act as the computational lead that enables the progress of research projects through insightful, timely, and relevant analysis of complex data that is communicated clearly. The role also requires ongoing awareness of new developments in the microbiome field that will improve Kaleidos data driven approach to interrogate and modulate the microbiome in a disease specific context.

Summary of Key Responsibilities:

  • Serve as computational biology lead for project support on translational and exploratory data analysis.
  • Provide data analysis for clinical studies, correlating microbial readouts with patient outcome.
  • Perform analysis of metagenomic data, community composition and gene annotations to guide project teams.
  • Actively participate in setting the directions for projects in a data driven way, changing directions if required
  • Effectively explain computational analyses and results to audiences of various levels of technical expertise
  • Collaborate closely with R&D Scientists to develop and test new hypotheses through in vivo and in silico experimentation
  • Provide a microbiome-oriented interpretation of data from various sources (metagenomics, metabolomics, etc.)
  • Manage workflows that involve outside partners and collaborators
  • Inform and guide Kaleidos omics strategy for interrogating microbial communities

  • Qualifications:

  • PhD in bioinformatics, microbial ecology, or related fields focusing on microbial genomics
  • Fluent in R or Python for microbial community analysis
  • Fluent working knowledge of software tools and trends in the metagenomics space (e.g. assemblers, mappers, annotation tools, etc.)
  • Experience recovering genomes from complex microbial communities
  • Experience analyzing multiple omics datasets
  • Experience analyzing microbial communities in the context of complex, multivariate data
  • Flexibility to meet shifting deadlines and prioritize tasks appropriately
  • A hunger to push yourself, and your team, to be the best analysts possible
  • A track record of innovation as evidenced by a strong publication record
  • Experience analyzing microbiome relevant data in a disease context is a plus
  • Comfortable using AWS cloud computing and cluster deployment is a plus
  • Use of various machine learning approaches for metagenomics data is a plus
  • Familiar with CAZy and dbCAN databases is a plus
  • Ecological modeling experience is a plus

  • Kaleido Biosciences is an EEO employer committed to an exciting, diverse, and enriching work environment.

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