Hello, my name is Vytautas!
I turn data into action. I'm an Analyst who builds machine learning models, creates efficient data pipelines, and uncovers hidden patterns to drive business success.
Check out my projects
My Tools / Stack
Python
JavaScript
Go
MySQL
Google Cloud Platform
Docker
My Background / About Me
My data journey began with business fundamentals at ISM University of Management and Economics, where I studied finance and learned the ins and outs of business processes. At Turing College, I gained expertise in data analysis, machine learning, and automation. After gaining industry experience, I returned to Turing College as a Mentor to give back to the community, where I now guide upcoming data experts through code reviews and technical challenges, helping them master the same path I took.
As an Analyst at Nord Security, I develop tools that help teams work better with data. I built data pipelines that automatically collect information from different sources like Ahrefs and YouTube. I also created a web scraper that, despite complex JavaScript rendering challenges, helps us understand what people are saying about our products across the internet, and a machine learning model that helps us find the right websites to work with.
To make our work easier, I created a centralized hub using React and PostgreSQL that, after solving complex state management and real-time data sync challenges, tracks daily API usage, automation script statuses, and marketing performance metrics for our growth operations. I also improved how we schedule and monitor our data processes, which reduced errors by 30% and saved time for everyone on the team.
Before this, I worked at CyberCare helping businesses use our products. This experience taught me how to communicate clearly with clients and understand what businesses need to succeed. I helped bring in over 200 new business clients and improved how we help our customers.
My Work / My Projects
Stroke Risk Prediction
Developed a machine learning model to predict stroke risk, identifying key factors and helping healthcare providers assess patient risk profiles.
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Travel Insurance Analysis
Developed a machine learning model to predict travel insurance purchases, identifying key factors in customer buying decisions.
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Red Wine Analysis
Applied machine learning techniques to analyze red wine chemistry, uncovering relationships between chemical properties and wine quality.
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Podcasts Analysis
Utilized Python and SQL to analyze podcast reviews, identifying key factors driving listener engagement and satisfaction.
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Mental Health Analysis
Investigated mental health trends in the tech industry using Python and SQL, identifying key issues and potential support strategies.
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COVID-19 Analysis
Conducted comprehensive analysis of South Korea's COVID-19 data, revealing pandemic patterns, spread dynamics, and demographic impacts.
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