Actuarial Analyst jobs in Oakville, IA

Title: Bioinformatics Analyst II

Location: Remote | Based in IL

Pay: $40-44/hr

Contract: 6 months

Focused 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.
• Curate, maintain, and contribute to the project codebase.

Qualification:

• Masters with 1 year of experience or PhD degree in the quantitative sciences (Bioinformatics, Computer Science, Computational Genetics, Mathematics, Statistics, or a related field).
• Proven capability in designing and implementing bioinformatics workflows and corresponding github codebase repositories.
• 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, e.g. p-value, odds ratio, effect size, multiple testing correction, familiarity with Bayesian approaches employed for colocalization analysis would be advantageous.
• Previous experience in immunological diseases or rare disease genetics is a plus.