Projects

Dzianis Makarevich

Welcome to My Data-Driven World

My journey into data science started with a fascination for uncovering patterns beneath the surface. With a background in Applied Data Science, project management, and marketing, I thrive at the crossroads of analytics, strategy, and business impact. Whether leading machine learning projects or translating data into actionable insights, I’m driven by the power of data to solve real-world problems. From predicting stock trends with hybrid models to analyzing customer behavior for retention strategies, I approach each challenge with curiosity, precision, and a passion for meaningful results. Today, I’m on a mission to connect technology and human behavior—creating solutions that are not just intelligent, but impactful.

Data Science

Data science transforms raw information into actionable insights—empowering smarter decisions and strategic innovation.

Predictive Modeling & Forecasting

Machine Learning & Deep Learning

Data Visualization & Decision Support

Project Management

Projects are driven by clarity, structure, and strategic alignment—ensuring objectives are met with precision and impact.

Strategic Planning & Execution

Risk Management & Agile Methods

Stakeholder Communication & ROI Tracking

Marketing

Data-driven marketing bridges customer needs with business goals—turning insights into engagement and measurable growth.

Consumer Insight & Market Research

Branding & Positioning Strategy

Digital Campaigns & Performance Metrics

2024

Hybrid Stock Market Prediction: Integrating Sentiment Analysis and Technical Indicators

Developed a machine learning-powered model that integrates sentiment analysis from social media and news with technical analysis of historical stock data. Leveraged LSTM, XGBoost, Linear Regression, and SVM to enhance prediction accuracy, surpassing standalone models. The project resulted in a robust tool for traders and investors, with future potential for real-time data integration and automated trading.

Customer Churn Analysis in the Banking Sector

Conducted an in-depth analysis to identify key factors driving customer attrition in the banking sector. Leveraged statistical techniques and machine learning (Logistic Regression) to develop a high-accuracy churn prediction model. Findings revealed a strong correlation between customer complaints and churn, emphasizing the need for enhanced complaint resolution strategies. This project provides actionable insights to improve customer retention and reduce churn, demonstrating the impact of data-driven decision-making in financial services.

2023

Life Expectancy Analysis: Statistical Comparison

Conducted a statistical analysis to compare the life expectancy of European men and women in 2011. Utilized a one-sample T-test to determine whether the average life expectancy of men was significantly lower than that of women. The analysis involved calculating sample mean, standard deviation, and hypothesis testing, leading to the rejection of the null hypothesis. This project highlights the application of statistical methods in demographic studies, providing insights into gender-based longevity differences.

2023

Hostage Situations and Counter-Terrorism Analysis

Conducted an in-depth analysis of hostage-taking incidents and related terrorist acts using the Global Terrorism Database. Collaborated with co-students to identify key factors influencing attack outcomes, weapon usage, and regional trends. The research provides valuable insights for policymakers, contributing to the development of effective counter-terrorism strategies and risk mitigation measures for future incidents.

2023

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Explored the application of widely used statistical methods in research to analyze and compare datasets. Utilized the T-test to assess differences in means between groups and the F-test to determine whether variances between populations were significantly different. This project highlights the importance of statistical techniques in identifying patterns, validating hypotheses, and driving data-driven insights across various fields.

2023

Productivity Analysis in the Textile Industry

Conducted a data-driven analysis of garment factory production to evaluate team productivity, departmental challenges, and the impact of incentive structures. Identified key factors such as rest days, idle time, and departmental workloads affecting efficiency. Provided actionable recommendations to optimize resource allocation, streamline operations, and enhance overall productivity in the textile industry.

2023

CPU Scheduling Algorithms Implementation

Developed a program implementing four key CPU scheduling algorithms: First-In-First-Out (FIFO), Shortest Job First (SJF), Priority, and Round Robin (RR). Each algorithm is designed to address different scheduling needs—FIFO ensures simplicity, SJF minimizes waiting time, Priority scheduling executes higher-priority processes first, and RR balances fairness and responsiveness. This project demonstrates the impact of scheduling strategies on system performance and process efficiency.

2023

Bank Prototype – Object-Oriented Programming (OOP)

Developed a bank prototype demonstrating the application of Object-Oriented Programming (OOP) principles to create modular, flexible, and extensible software. Utilized encapsulation, inheritance, polymorphism, and abstraction to enhance adaptability, maintainability, and scalability. This project highlights how OOP fosters efficient software design, ensuring long-term usability and ease of future enhancements.

2023

Customer Imputer – Strategy and Factory Pattern

Developed a custom-built imputer using Object-Oriented Programming (OOP) principles, implementing the Strategy and Factory design patterns for flexible and efficient data preprocessing. The tool automates tasks such as transposing data, converting strings to integers, and imputing missing values. Its modular architecture allows users to customize functionality with different imputation strategies, including mean, mode, and median-based approaches. This project enhances data preparation workflows, ensuring adaptability for various analytical needs.

2023

Fake News Detection – NLP with BERT

Developed a machine learning-based fake news detection system using Natural Language Processing (NLP) with BERT. The project explored the effectiveness of BERT in identifying misinformation, demonstrating strong performance but highlighting challenges with unseen datasets. Provided valuable experience in data science and misinformation analysis, with future plans to develop a web application for real-time classification of news as "Real" or "Fake."

2023

New York Medallion Taxi Analysis Report

Conducted an in-depth analysis of New York yellow taxi demand trends, peak periods, and revenue patterns. Utilized descriptive statistics for visualization and predictive models, including Linear Regression, Polynomial Regression, and Random Forest, to uncover key insights. The report examines the impact of extreme weather events, such as record blizzards, on taxi operations and emphasizes the importance of data cleaning and normalization for accurate industry analysis.

2023

Evaluation and Recommendation of a Learning Management System (LMS) for Gokstad Akademiet

Conducted a comprehensive evaluation to recommend an optimal Learning Management System (LMS) for Gokstad Akademiet, focusing on enhancing flexibility, accessibility, and student engagement in online learning. Utilized strategic analysis, benchmarking, and stakeholder feedback, supported by literature reviews and expert consultations, to compare various LMS platforms. Despite challenges such as delays and communication gaps, a structured approach ensured a well-supported evaluation report, providing actionable insights for effective LMS implementation.

2023

Project Initiation and Definition: Methods and Approach

This project focused on structured project initiation and selection, emphasizing strategic alignment with organizational goals. It employed financial assessments such as payback period analysis, qualitative scoring models, and risk-based categorization to evaluate project viability. Key methodologies included Work Breakdown Structure (WBS), project mandate development, and benefits realization planning, applied to a case study on an ergonomic office chair. This approach provided a systematic framework for project evaluation, enhancing decision-making and improving success rates.

2023

Empowering Decisions with Intelligent Insights