Sara Evans
About Sara Evans
Sara Evans is a Business Intelligence Data Analyst II at DNSFilter, specializing in machine learning and deep learning using Python. She has a background in data science and biology, with experience in various analytical roles and research projects.
Work at DNSFilter
Sara Evans has been employed at DNSFilter as a Business Intelligence Data Analyst II since 2022. In this role, she utilizes her expertise in data analysis to support business intelligence initiatives. Her work involves remote collaboration with team members to analyze data trends and provide insights that drive decision-making within the organization.
Education and Expertise
Sara Evans holds a Bachelor's degree in Biology and Data Science from the University of North Carolina at Wilmington, where she studied from 2018 to 2020. She further enhanced her skills in data science by completing the Data Scientist with Python Career Track at DataCamp. Her technical expertise includes machine learning with Python's scikit-learn and deep learning with Keras.
Background
Sara Evans began her academic journey at New York University from 2015 to 2018 before transferring to the University of North Carolina Wilmington. During her time at UNC Wilmington, she engaged in various roles, including Student Researcher and Digital Projects Assistant. She also worked as an Analyst at Urban Science from 2020 to 2022, where she applied her analytical skills in a professional setting.
Achievements
Sara Evans contributed to the development of the statistical R package SongEvo, which models cultural song evolution in bird populations. This project integrated various factors, such as female mate choice and cultural learning. Additionally, she participated in a NOAA-sponsored workshop that focused on data collection and analysis for the Marine Fisheries Service, highlighting her commitment to balancing societal needs with marine resource sustainability.
Personal Projects and Interests
Outside of her professional work, Sara Evans engages in personal projects that reflect her interests. She tends to a fungi farm and experiments with new recipes, showcasing her passion for hands-on activities and continuous learning. Her commitment to self-directed learning is evident, as she has accumulated over 100 hours of study in data processing and analysis through platforms like DataCamp.