Bioinformatics Data Scientist
A bioinformatics data scientist is responsible for providing experimental design consulting and data analysis for large, high-throughput genomic experiments, with a focus on forensics and metagenomics. The bioinformatics data scientist will be responsible for designing and implementing annotated code for managing, manipulating, and analyzing large-scale genomic data, and for preparing thorough documentation and reporting.
- Develop tools for management, analysis and interpretation of high-density microarray and whole genome sequencing data.
- Managing, manipulating, analyzing data using a combination of R, python, and UNIX tools.
- Using established domain-specific open-source software and tools to manipulate and analyze genomic data.
- Implement and execute data processing workflows and automated analytic pipelines.
- Create standardized summary tables and figures using literate programming and reproducible workflows.
- Conduct workflow benchmarking and documentation, identifying inconsistencies and resolving data problems.
- Prepare SOPs, document source code/workflows, and write reports to summarize computational
requirements, processing status, and customized analysis results.
Experience and Qualifications
Required Knowledge, Skills & Abilities:
- Expert proficiency working in a Unix/Linux environment.
- Expert proficiency with R, RMarkdown, and the “tidyverse” tools for data analysis.
- Advanced proficiency with open-source software, tools, and databases for analyzing next-generation sequencing data (whole-genome sequencing, RNA-seq, epigenetics, microbiome, and metagenomics).
- Proficiency working with and developing using Docker and/or Singularity container technology.
- Proficiency using version Control software (e.g., Git or similar) to manage programming code.
- Proficiency with Python, Perl, or another scripting language.
- Preferred: Experience with NextFlow, SnakeMake, or similar workflow/pipeline management systems.
- Preferred: Familiarity with developing and querying relational databases.
- Preferred: Familiarity with AWS and/or Azure cloud computing.
- MS or PhD in Bioinformatics, Genomics, Data Science, or related field
- Experience (5+ years with MS or 3+ years with PhD) managing and analyzing large-scale datasets produced sequencing platforms and deliver solutions for managing, visualizing, analyzing, and interpreting genomic data
- Advanced experience using Linux/Unix text processing tools, R, and other open-source tooling to manipulate and format data, to assess data quality, and analyze data.
- This position requires that the candidate be willing and able to complete a successful background screening for a security clearance. Candidates with a current security clearance will receive preference.
- Health Tech & Software