Data Scientist with a Biology Background | Python, R, Machine Learning | Analyzing Complex Data for Actionable Insights | Published Researcher in BiologyI bring a unique perspective to the field. With a passion for solving complex puzzles, I thrive on deciphering the stories hidden within data and transforming them into meaningful insights. Leveraging my Python, R, and machine learning expertise, I tackle full-stack data science projects, applying statistical analysis and developing predictive models to extract valuable information from diverse datasets.Throughout my career, I have completed projects that have made a real-world impact. For instance, I developed a machine learning model using Tensorflow to detect real-time stress levels from wearable device data, improving the development and design of such devices by identifying critical features in stress detection. Additionally, I utilized convolutional neural networks (CNNs) to identify pneumonia in chest X-ray images, aiming to increase diagnostic speed and accuracy. I have also applied machine learning techniques to predict vaccination hesitancy, providing valuable insights into public health trends.Before transitioning into data science, I excelled as an Assistant Professor, teaching and advancing student knowledge in microbiology. As a Postdoctoral Research Fellow, I enhanced our understanding of protein behavior in cell biology by analyzing fluorescent and confocal micrographs. I earned a Ph.D. in biology for my research on gene copy numbers in microorganisms, contributing to a deeper understanding of microbial genetics and evolution.With my extensive academic and industry background, I possess strong communication skills and thrive in collaborative environments. I am constantly eager to tackle new challenges and excel at bridging the biology and data science gap. Let's connect and explore potential opportunities if you want a data scientist who can bring a unique interdisciplinary perspective and deliver actionable insights.