Data Analyst with less than a year in Data Analytics & Machine Learning
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Business Data Analytics undergraduate at IIT (offered by University of Westminster) with strong skills in data analytics, statistical analysis, and machine learning. Proficient in Python and SQL, with the ability to turn complex data into actionable business insights. Passionate about applying data-driven solutions to real-world business challenges.
University of Westminster
BSc (Hons) · Business Data Analytics
August 1, 2025 – Present
Yasodara Devi Balika Maha Vidyalaya
GCE Advanced Level · Physical Science
June 1, 2014 – May 31, 2023
Yasodara Devi Balika Maha Vidyalaya
GCE Ordinary Level
June 1, 2014 – May 31, 2023
Amara Hardware
Inventory & Operations Assistant
January 1, 2023 – Present
Gampaha, Western Province, Sri Lanka
Amara Electricals and Paints
Retail Operations & Sales Associate
January 1, 2023 – Present
Gampaha, Western Province, Sri Lanka
Hospital Readmission Risk Prediction Mini Group Project R | Logistic Regression
January 1, 2025 – June 1, 2026
Performed data preprocessing, built and compared logistic regression models, and identified key risk factors including prior hospitalizations, diabetes medication use, and patient age, achieving 60.6% model accuracy.
Data Story – Mortality Trends in England and Wales
January 1, 2025 – June 1, 2026
Analyzed 10 years of ONS mortality data across gender, age group and cause of death using Power BI. Designed and interpreted 6 professional visualisations including heat maps, area charts and clustered column charts. Cleaned and prepared raw ONS datasets by removing redundant rows and recalculating percentage columns. Analyzed the dataset with a full report.
Education Progress Across South Asia – Interactive DashboardData Visualization Module
January 1, 2024 – June 1, 2026
Built an interactive Power BI dashboard tracking education access, completion, and quality across 8 South Asian countries (2010–2024). Visualized completion rates by education level and gender, teacher quality, Gender Parity Index (GPI), and pre-primary participation. Incorporated forecasting trends and country-level comparisons using UNESCO and World Bank datasets.
Multidimensional Analysis of Sri Lanka's Emissions Data Using Interactive Visualization Techniques
January 1, 2023 – June 1, 2026
Conducted a comprehensive data analysis of Sri Lanka's CO2 emissions dataset, including data cleaning, transformation, and exploratory analysis. Developed an interactive Streamlit dashboard using Python, Pandas, and Plotly with dynamic filtering, KPI metrics, and advanced visualizations (treemaps, trends, sector breakdowns) to support data-driven decision-making. Generated automated analytical insights (dominant sectors, emission hotspots, year-on-year trends) and deployed a responsive dark-themed application with CSV export and Streamlit Cloud integration.
Foodz@Yourz
January 1, 2023 – June 1, 2026
Designed a comprehensive Conceptual EERD for a multi-store grocery service, utilizing advanced specialization and generalization to model complex product hierarchies, staff roles, and delivery logistics. The system integrates member management and payment processing, supported by a detailed Data Dictionary and strict EERD constraints to ensure a robust relational database design.
BoilHeaterz
January 1, 2023 – June 1, 2026
Mapped a Conceptual EERD into a fully normalized logical schema for a heating maintenance provider, featuring 13 interrelated tables that manage customers, engineers, and spare parts. Using draw.io, I established strict referential integrity through precise key definitions and cardinality constraints to ensure the design is fully implementable within an Relational Database Management System.
Cultural Fit Analysis
The candidate's academic background in Business Data Analytics and diverse project portfolio (emissions data, education progress, mortality trends, grocery service EERD, heating maintenance EERD) indicate a broad interest in applying data analysis across various domains. This adaptability and curiosity suggest a good cultural fit for an organization that values continuous learning and diverse problem-solving approaches. The academic nature of all projects, however, means real-world team collaboration and project management experience are not evident.
Soft Skills & Operational Fit
The candidate's academic projects demonstrate an ability to work with diverse datasets and apply analytical techniques to solve business problems. The retail operations experience, while not directly technical, suggests an understanding of business processes and potentially customer interaction, which can be valuable in understanding data requirements. However, the lack of professional experience in a data analyst role means operational fit for a senior role is unproven.