Job Description

About the Role:

We are seeking a highly skilled and experienced Genetic Data Analyst to join our team. In this role, you will be responsible for performing in-depth analysis of genetic and genomic data, ensuring data quality, conducting QTL and population genetics analyses, and integrating genetic datasets with other omics data. This position requires a deep understanding of genetics, bioinformatics, and computational tools. The ideal candidate will have a Ph.D. in Genetics, Genomics, Computational Biology, or a related field, along with over 5 years of hands-on experience in genetic data analysis.

Key Responsibilities:

Data Acquisition & Ingestion: Query and retrieve genetic and genomic datasets from external databases and public repositories.

Genetic/Genomic Data Analysis: Conduct quality control and downstream analysis of high-throughput genetic/genomic data.

QTL Analysis: Perform quantitative trait loci (QTL) analyses to identify genetic markers associated with complex traits.

Population Genetics: Analyze population-level genetic variation, structure, and diversity.

Data Integration: Merge genetic datasets with transcriptomic, proteomic, and other omics data for multi-dimensional analysis.

Documentation & Reporting: Maintain thorough documentation of methodologies, pipelines, and findings. Prepare reports and presentations for internal and external stakeholders.

Education & Qualifications:

Minimum Required: Ph.D. in Genetics, Genomics, Computational Biology, Bioinformatics, or a closely related field.

Pay Range:

$80 - $100 an hr.

Required Skill & Competencies:

Strong proficiency in genetic/genomic data analysis tools and methodologies.

Expertise in programming languages such as R, Python, and Bash.

Hands-on experience with high-performance computing (HPC) environments and Cloud Computing.

Solid understanding of statistical methods used in genetic data analysis.

Excellent written and verbal communication skills, with the ability to clearly convey complex data to diverse audiences.

Preferred Qualifications:

Experience working with real-world human, animal, or plant genetic datasets.

In-depth knowledge of statistical genetics principles and methodologies.

Practical experience or strong interest in Artificial Intelligence (AI) and Machine Learning (ML) applications in genetics.

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