![How to Use GA4 to Track Social Media Traffic: 6 Questions, Answers and Insights [VIDEO]](https://www.orbitmedia.com/wp-content/uploads/2023/06/ab-testing.png)
![How Human Behavior Impacts Your Marketing Strategy [Video]](https://contentmarketinginstitute.com/wp-content/uploads/2025/03/human-behavior-impacts-marketing-strategy-cover-600x330.png?#)
![How to Make a Content Calendar You’ll Actually Use [Templates Included]](https://marketinginsidergroup.com/wp-content/uploads/2022/06/content-calendar-templates-2025-300x169.jpg?#)
![Building A Digital PR Strategy: 10 Essential Steps for Beginners [With Examples]](https://buzzsumo.com/wp-content/uploads/2023/09/Building-A-Digital-PR-Strategy-10-Essential-Steps-for-Beginners-With-Examples-bblog-masthead.jpg)
Remote Senior Scientist, Statistical Genetics
A company is looking for a Remote Senior Scientist in Statistical Genetics. Key Responsibilities Lead strategies for population-scale genetics and genomic datasets, including Real-World Evidence data Design and implement genetic statistical methods for GWAS/RVAS and integrate multiple omics data Collaborate with cross-functional teams to validate disease mechanisms and provide insights into drug development Required Qualifications Ph.D. in statistical genetics, bioinformatics, or computational biology with at least 2 years of experience Proven experience in analyzing high-dimensional genomics data Strong foundational knowledge of population genetics and experience with human genetic DNA sequencing data Hands-on programming skills in Python and/or R/Bioconductor, with experience in Unix and cluster computing Prior experience with large-scale human genetics studies is strongly preferred
A company is looking for a Remote Senior Scientist in Statistical Genetics.
Key Responsibilities
Lead strategies for population-scale genetics and genomic datasets, including Real-World Evidence data
Design and implement genetic statistical methods for GWAS/RVAS and integrate multiple omics data
Collaborate with cross-functional teams to validate disease mechanisms and provide insights into drug development
Required Qualifications
Ph.D. in statistical genetics, bioinformatics, or computational biology with at least 2 years of experience
Proven experience in analyzing high-dimensional genomics data
Strong foundational knowledge of population genetics and experience with human genetic DNA sequencing data
Hands-on programming skills in Python and/or R/Bioconductor, with experience in Unix and cluster computing
Prior experience with large-scale human genetics studies is strongly preferred