Rachel L.

Software Engineer @ DNAnexus

About Rachel L.

Rachel L. is a Software Engineer at DNAnexus, where she contributes to data-driven software solutions. She has a background in data science and has held various roles, including mentoring aspiring data scientists and participating in community outreach to promote STEM education.

Work at DNAnexus

Currently, Rachel L. works at DNAnexus as a Software Engineer, a position she has held since 2022. In this role, she contributes to the development of software solutions, focusing on data-driven projects. Her work supports the company's mission to advance genomic data analysis and improve healthcare outcomes through innovative technology.

Education and Expertise

Rachel L. studied at the University of California, Berkeley, where she earned a Bachelor of Arts in Data Science from 2017 to 2021. During her studies, she developed a capstone project that utilized machine learning techniques to address real-world problems. Her educational background provides a strong foundation in data science and computer science.

Background in Data Science and Engineering

Rachel has a diverse background in data science and engineering. She has held various roles, including Data Analyst Intern at Keenan in 2019 and Data Engineer at Fidelity Investments from 2021 to 2022. Additionally, she worked as a Data Science and User Experience Researcher at Goodly Labs in 2019. Her experiences span multiple organizations and projects, showcasing her versatility in the field.

Mentorship and Community Engagement

Rachel L. has volunteered as a mentor for aspiring data scientists through university-led initiatives. While at UC Berkeley, she engaged in community outreach programs aimed at promoting STEM education among underrepresented groups. Her commitment to mentorship reflects her dedication to fostering the next generation of data science professionals.

Hackathons and Competitions

During her time at UC Berkeley, Rachel participated in hackathons and coding competitions, demonstrating her skills in data science and computer science. These experiences allowed her to apply her knowledge in practical settings, collaborate with peers, and enhance her problem-solving abilities.

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