Job Title: Bioinformatic Analyst II
Location: Remote
Duration: 6 months
Pay Range: $38-$40/hour

Job dscription:
Bioinformatics/Computational Biologist (w/ focus on Genetics)

Services Overview:

• This role involves support for the integration, organization, and analysis of large and complex multi-omics datasets, but not limited to transcriptomics, genetics, and epigenetics.
• A vital part of this role includes ensuring the precision, quality, and comprehensiveness of our dataset repositories.
• The successful candidate will work in synergy with cross-functional and inter-organizational teams of research scientists.
• They will apply, refine, and expand established workflows for effective multi-omic data curation and analysis.

Key Responsibilities:

• Curate and standardize GWAS summary statistics datasets ensuring accuracy and consistency.
• Annotate genomic variants using established tools and databases.
• Map SNPs to genes and determine their functional relevance.
• Analyze transcriptomic datasets, including but not limited to bulk and single-cell RNA sequencing, to derive actionable insights.
• Collaborate intimately with research teams to comprehend specific data requirements and applications.

Qualification:

• Master’s with 1+ year of experience or PhD degree in the quantitative sciences (Bioinformatics, Computer Science, Computational Genetics, Mathematics, Statistics, or a related field).
• Candidate with bachelor’s degree with 3+ years relevant experience can be considered.
• Proven capability in designing and implementing bioinformatics workflows.
• Proficiency in R programming and comfortable operating in a Unix/Linux and High-Performance Computing (HPC) environment.
• Familiarity with genome-wide association studies, particularly in fine mapping and colocalization from GWAS summary data is expected.
• Hands-on experience in curating and processing transcriptomic datasets, especially bulk and single-cell RNA-Seq, with the ability to conduct corresponding downstream analyses would be advantageous.
• Knowledge and proficiency in basic statistical concepts.
  Previous experience in immunological diseases or rare disease genetics is a plus.

What are the top 3-5 skills, experience or education required for this position:

• Strong proficiency in R programming for bioinformatics workflows
  Familiarity with curating/analyzing multi-omic data, particularly genetics data modalities.
• Ability to critically evaluate experimental design, QC and suggest improvements.
• Experience working in HPC or cloud environment
• Knowledge and proficiency in basic statistical concepts.

What is a nice to have (but not required) regarding skills, experience, education, or certification:

• Experience in immunological disease area.