Bioinformatics Scientist

St. Paul, Minnesota
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Type: Direct-Hire

Category: Information Technology

Job ID: 140769

Date Posted: 05/15/2019


Title: Bioinformatician

Type: Direct, Full-time salaried with benefits

Location: Saint Paul, MN

Start Date: Immediate

Our client, a genomics technology provider, is looking for a Bioinformatician to join their team for a full-time opportunity. 


This position will involve carrying out bioinformatic and statistical analysis of multi-omic data using cloud-based computing for internal and external projects. Successful applicants will be expected to work collaboratively as part of a team, and to use software engineering best practices to ensure the utmost standard of quality and reproducibility. A strong preference is for applicants that have expertise in microbiome analysis, data visualization and statistical analysis.

Specific analysis efforts will include:

  • Analysis of microbiome data for unique and specialized projects
  • Multi-omics approaches including genomic, metabolomic and microbiome data (amongst others)
  • Testing and implementing novel analysis methodologies
  • Working closely with team members and customers to find biological signals in data


  • 3 + years working with microbiome datasets and evaluating and implementing metagenomics computational tools as evidenced by publication(s) in the field.
  • 3+ years of experience in academic or industry laboratory setting.
  • Proficient in R, Python, and Unix.
  • Graduate-level education or post-graduate training in computational biology, bioinformatics, statistics, microbiology or related field.
  • Experience with Amazon Web Services including EC2, S3, EC2 Container service.
  • Practical experience with coding best practices and reproducible research.
  • Passionate about data analysis and visualizations.
  • Ability to manage time and meet deadlines on multiple projects at the same time.
  • Strong attention to detail.
  • Strong communication skills and ability to work effectively on a team.
  • Ability to present data to non-scientific audiences.


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