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.