psydoc19 / portfolio

Hello! I'm Vitalii Diakonov, a Miami-based Data Scientist. Armed with a Master's in Data Science, along with a Doctorate in Medicine and a Master's in Economics, I blend diverse expertise into insightful data-driven projects. Explore this repository to witness my multidisciplinary approach in action.

Vitalii Diakonov's portfolio

Introduction

Greetings! I am Vitalii Diakonov, a passionate Data Scientist based in the vibrant city of Miami, USA. My academic foundation is rooted in Medicine, followed by specialized studies in Economics, and further augmented with a Master's degree in Data Science. This diverse educational trajectory provides me with a multifaceted perspective, enabling me to deliver insights that harmoniously integrate across various disciplines.

About this Repository

This GitHub repository serves as a window into my professional journey and showcases a curated collection of my public projects. Each project encapsulates my dedication to leveraging data-driven methodologies to derive actionable insights, solve intricate problems, and drive meaningful change across diverse domains.

What to expect

As you navigate through this repository, you'll encounter a variety of projects that reflect my versatility as a data scientist. Whether it's analyzing intricate datasets, developing predictive models, or uncovering patterns to inform strategic decisions, each project encapsulates a facet of my expertise.

Projects highlights

• Asthma Study Using the 2022 BRFSS Survey Data in R: A deep dive into the Behavioral Risk Factor Surveillance System data to explore the multifaceted nature of asthma. This project showcases my ability to navigate through a vast dataset, apply logistic regression, and uncover insights that bridge the gap between data science and public health. The study revealed significant associations between asthma prevalence and factors such as race/ethnicity, sex, BMI category, and smoking status, contributing valuable insights to the field of medical data science.

• Salifort Motors in Python: This data analysis delves deep into understanding the intricacies of employee workload, satisfaction levels, and the consequent impact on retention rates within the automotive organization. Utilizing advanced data modeling techniques and analytics, the project aims to pinpoint critical factors that influence employee satisfaction and, subsequently, provide actionable strategies to enhance organizational well-being.

• Data Cleaning and Transformation Project in R: for the "Human Activity Recognition Using Smartphones" project. This project involves merging datasets, extracting mean and standard deviation measurements, assigning descriptive activity names, and creating a tidy dataset containing the average value of each variable for each activity and subject.

Get in touch

I am always eager to collaborate, share insights, and explore opportunities that align with my passion for data science. Feel free to reach out via LinkedIn or Email to initiate a conversation or discuss potential collaborations.

Acknowledgments

I extend my gratitude to the data science community, mentors, and peers who have enriched my journey with invaluable insights, feedback, and collaborative opportunities.

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