Beibei(bella) D.
About Beibei(bella) D.
Beibei (Bella) D. is a Genomic/AI Intern with a strong background in data science and engineering, currently working at Tenaya Therapeutics and DataOceans. She possesses skills in Python, R, SQL, AWS, and TensorFlow, and has experience in various roles across healthcare and academic institutions.
Work at Tenaya Therapeutics
Currently, Beibei D. serves as a Genomic/AI Intern at Tenaya Therapeutics in South San Francisco, California. This role commenced in 2023 and is conducted on-site. As part of her internship, she is involved in the DUKE MIDS Capstone Project, which focuses on applying genomic and artificial intelligence methodologies.
Education and Expertise
Beibei D. is pursuing a Master's degree in Interdisciplinary Data Science at Duke University, expected to complete in 2024. She holds a Bachelor of Science in Probability and Statistics and has studied cognitive science with a focus on machine learning and neural computation at UC San Diego. Additionally, she has received multiple certifications from Coursera and DataCamp in statistics and data science.
Background
Beibei D. has a diverse educational background, having attended multiple institutions. She graduated from Southwestern Academy and Crean Lutheran High School, earning high school diplomas. Her academic journey includes significant time at UC San Diego, where she studied various disciplines related to data science and cognitive science.
Professional Experience
Beibei D. has accumulated extensive experience in data-related roles. She worked as a Data Engineer at DataOceans and previously held positions as a Data Scientist at Envita Fertility Center and a Research Assistant at San Diego VA Medical Center. Her experience also includes teaching assistance at Duke University and laboratory assistance at Gen 5 Fertility Center.
Achievements
Beibei D. received an academic scholarship for outstanding students during her Master's program at Duke University. She has demonstrated her skills in data collection, documentation, analysis, and visualization across various roles, showcasing her commitment to solving data-driven problems, particularly in healthcare and finance sectors.