About

Vignesh Ramchandran is a highly skilled Data Scientist, Statistician, and aspiring Product Analyst with a passion for leveraging data and analytics to build great products, engage and retain users, and support data-driven decision making. He recently graduated from Penn State University with a Ph.D. in Environmental Health, where he specialized in analyzing the outcomes of toxicology experiments using statistical models, machine learning, and optimization heuristics to improve public health policy. Currently a Data Science Fellow at Insight Data Science, Vignesh has built and deployed a playlist label recommender for new, emerging songs on Spotify based on a user's music library, serving as potential proof of concept for a future product feature. He has also worked as a Graduate Researcher and Graduate Teaching Assistant at Penn State University, where he gained valuable experience in conducting research, designing experiments, and teaching undergraduate students. With over 4.60 years of relevant experience, Vignesh is well-versed in a range of technologies and tools, including Data Science, Research Scientist, ML, SQL, AWS, Naive Bayes, Random Forest, Seaborn, Scikit, test, Python, Pandas, and Web. He is also an active contributor to the open-source community, with a GitHub profile showcasing his projects and contributions. In summary, Vignesh is a highly motivated and enthusiastic Data Scientist and Statistician with a proven track record of leveraging data and analytics to build great products and make better decisions. He is always eager to learn and grow, and is committed to delivering high-quality solutions that meet the needs of his clients and stakeholders.