Assist in analyzing Ancestry’s massive-scale genomic datasets to help uncover deep insights into population structure, demographic history, and fine-scale genetic relationship inference.
Apply and/or develop novel statistical models and computational methods, including Machine Learning and Deep Learning approaches, to solve complex genomics challenges.
Engage in exploratory research, learning to navigate complex research while maintaining a focus on identifying next steps and demonstrating progress towards research milestones.
Contribute to the work that will be published in scientific journals and present at conferences.
Collaborate with our research team to explore how your work can contribute to the Ancestry DNA product ecosystem and the broader scientific community.

Currently enrolled in a Graduate program (Ph.D. preferred, or MS) in Population Genetics, or Genomic Data Science, or Machine Learning with an interest in applying it to genomics.
Experience in applying computational and statistical methods to genomic datasets.
Experience with modern AI methods is a plus.
Strong programming skills in Python or other languages that support efficient, large-scale data analysis and machine learning.
A mindset for critical thinking and innovation and the ability to demonstrate progress on exploratory tasks.
Ability to work up to 50% of your time at Ancestry while successfully balancing your graduate studies.
Good communication skills and a desire to learn how to present complex genomics and statistical concepts to various audiences.

Graduate Research Co-op, Population Genetics, Genomic Data Science

Key skills