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Data Science with less than a year in Data Analysis & Machine Learning
Third-year Data Science undergraduate at SLIIT with a 3.82 GPA and three Dean's List awards (4.00 GPA in both Year 2 semesters). Experienced in building end-to-end data pipelines, designing dimensional data warehouses, and developing Power BI dashboards for business reporting. Applied machine learning experience through a statistical modelling research project comparing five predictive models with cross-validated evaluation. Strong foundation in mathematics, statistics, and software engineering, with a track record of leading technical project teams from design through deployment.
Sri Lanka Institute of Information Technology (SLIIT)
BSc (Hons) Information Technology · Data Science
August 1, 2023 – Present
University of Peradeniya
BSc · Physics, Computer Science, Mathematics
August 1, 2023 – Present
Dharmaraja College
G.C.E. Advanced Level · Physical Science Stream
N/A – May 31, 2021
Smart Campus Operations Hub (UNI PULSE)
April 1, 2026 – May 1, 2026
Led design and development of a full-stack platform with booking workflow, conflict detection, real-time notifications, Google OAuth 2.0, and role-based access control (User / Admin / Technician). Directed REST API design in Spring Boot, the React.js front end, and a GitHub Actions CI/CD pipeline end-to-end.
End-to-End Customer Churn Analysis Dashboard & Machine Learning Prediction System
January 1, 2026 – June 1, 2026
Developed SQL-based ETL pipelines, staging/production tables, and analytical views to clean, transform, and prepare telecom customer data for reporting and predictive modelling. Designed interactive Power BI dashboards with DAX measures, Power Query transformations, drill-through insights, tooltips, and executive-level KPI visualisations for customer retention analysis. Performed exploratory data analysis (EDA) to identify churn patterns across demographics, contracts, services, tenure, and geographic regions. Trained and evaluated a Random Forest classification model achieving 84% accuracy, using feature engineering, label encoding, confusion matrix analysis, and feature importance evaluation. Predicted 378 potential future churners and integrated model outputs into Power BI dashboards to support data-driven retention strategies.
Online Clothing Store Management System
July 1, 2025 – October 1, 2025
Built a full-stack e-commerce platform with a 3D cloth customiser (Three.js), inventory management, supplier management, and JWT-secured authentication.
Statistical Modelling Research: Data Maturity & Organisational Confidence
January 1, 2025 – January 1, 2026
Led a team of 4, analysing 1,000+ companies across 18 variables to quantify how data maturity drives organisational confidence. Built a full analytics pipeline in R: Pearson correlation (r = +0.954), simple linear regression (R2 = 91%), one-way ANOVA (F = 1059, p < 0.001). Compared 5 predictive models (MLR, Ridge, Decision Tree, Random Forest, Gradient Boosting); the best model achieved 5-fold CV R2 = 0.917 ± 0.008 with zero overfitting. Key finding: Level 5 firms averaged 99.3% confidence vs. 29.9% at Level 1 a 69-point gap.
Data Warehousing & Business Intelligence System
January 1, 2025 – January 1, 2026
Designed a production-grade star schema data warehouse with 1 fact table and 4 dimension tables (~30,000 fact rows), including SCD Type 2 historical tracking. Built a 3-layer ETL pipeline (TXT, CSV, XLSX → Staging → DW) using modular SSIS packages with lookup and conditional split transformations. Deployed an SSAS multidimensional cube and demonstrated all 5 OLAP operations via Excel PivotTables. Published 4 Power BI reports to Power BI Service with custom DAX measures, including average mark, pass rate %, and total students.
View ProjectDean's List - Year 2, Semester 2 (GPA: 4.00)
SLIIT
May 1, 2026 – Present
Dean's List - Year 2, Semester 1 (GPA: 4.00)
SLIIT
January 1, 2026 – Present
Dean's List - Year 1, Semester 1 (GPA: 3.86)
SLIIT
October 1, 2024 – Present
Kids, Junior, Senior & Open Athletics Championships 2013
Kandy District Athletics Association
October 1, 2023 – Present
All Island Graded Examination - Spoken English (91/100)
Institute of Western Music and Speech
September 1, 2010 – Present
Cultural Fit Analysis
The candidate's diverse academic projects, ranging from e-commerce to smart campus operations and in-depth data science research, indicate a broad interest and adaptability. Their involvement in various clubs and sports suggests a well-rounded individual who can contribute positively to team environments. The focus on end-to-end solutions in projects aligns with a proactive and results-oriented culture. The candidate's academic background in both Physics/Computer Science/Mathematics and Data Science provides a strong interdisciplinary foundation, which can be valuable in diverse technical teams.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, problem-solving, and teamwork skills through their involvement in academic clubs and leadership roles in projects. Their ability to lead technical teams from design to deployment suggests good operational fit and project management potential. The detailed descriptions of project methodologies (e.g., cross-validated evaluation, ETL pipeline layers, OLAP operations) indicate a structured and thorough approach to technical work. The candidate's consistent high academic performance also points to diligence and a strong work ethic.