Job Description
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 GWAS and genetics data, and transcriptomics data.
· 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.
· 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.
· 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.
Company DescriptionCollabera is a Global Digital Solutions Company providing Software Engineering Solutions for the world's most tech-forward organizations in the areas of Engineering, Cloud and Data/AI. With its roots serving the engineering needs of the world's most recognized businesses in Technology, Financial Services, Telecom and Healthcare, Collabera today operates across 60 locations in 11 countries, serves 30% of the Fortune 500, and has exceeded the industry growth rate by 3-4x for several years.
Collabera is a Global Digital Solutions Company providing Software Engineering Solutions for the world's most tech-forward organizations in the areas of Engineering, Cloud and Data/AI. With its roots serving the engineering needs of the world's most recognized businesses in Technology, Financial Services, Telecom and Healthcare, Collabera today operates across 60 locations in 11 countries, serves 30% of the Fortune 500, and has exceeded the industry growth rate by 3-4x for several years.
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