Pranav Arumai Raj

Personal Statement

A driven Computer Science student with hands-on experience in machine learning model development, data analysis, IoT systems, and software engineering. Strong foundation in algorithms, data structures, and object-oriented programming in Python, C++, and R. Adept at making data-driven decisions, leading technical teams, and delivering results in fast-paced, collaborative environments. Actively seeking a Summer 2026 internship to contribute technical expertise and grow within an innovative professional environment.

Key Expertise

Languages C++ · C · Python · R · Java · SQL (Oracle PL/SQL)
Data & ML KNN · Random Forest · Decision Trees · Logistic Regression · Naive Bayes · Feature Engineering · Data Preprocessing · Data Visualisation
ML Frameworks RStudio · Learning TensorFlow, JAX & Transformer-based architectures
Networking IPv4 Subnetting · VLANs · Routing Protocols · 802.11 WLAN · TCP/UDP · Packet Switching
Hardware / IoT Raspberry Pi · Sensor Integration · GPIO · Network Configuration
Tools & Methods Taiga (Agile/Scrum) · Git/GitHub · Linux Terminal · PyCharm · GitHub Copilot · Power BI · Jira

Project Experience

Data Analyst | Diabetes Prediction — Comparative ML Study
R, RStudio, caret
  • Built an end-to-end ML pipeline on a clinical dataset of 16,969 records — handling missing value imputation, Z-score outlier detection, and upsampling to correct severe class imbalance.
  • Designed and evaluated five classification models — Logistic Regression, KNN, Naïve Bayes, Decision Tree, and Random Forest — using Kappa as the primary metric to avoid misleading accuracy scores on imbalanced data.
  • Identified Random Forest as the optimal model, achieving 99.85% accuracy and a Kappa of 0.9605 with Specificity of 95.38% — outperforming literature benchmarks of ~94%.
  • Applied Gini Importance analysis to identify Blood Glucose and Age as the strongest predictors; demonstrated that high model Sensitivity (0.9994) is critical in clinical settings to minimise false negatives.
Team Lead | Smart Agriculture IoT System
Raspberry Pi, Python, GPIO, Taiga
  • Led a team of 4 to design and build an automated plant-monitoring system using Raspberry Pi sensor modules to optimise crop yields and water conservation.
  • Engineered the data pipeline for soil moisture and atmospheric particulate sensors, enabling real-time monitoring of hydration levels and environmental health.
  • Developed a dynamic alerting system that informed users exactly when and where irrigation was required, reducing potential water waste.
  • Facilitated Agile workflows using Taiga for project management, overseeing backlog grooming, sprint planning, and task delegation to ensure consistent project velocity.
Database Developer | Relational Database Design
Oracle, SQL (PL/SQL)
  • Wrote complex SQL queries including multi-table joins, subqueries, and aggregate functions to extract business insights and ensure data integrity.
  • Created Entity-Relationship Diagrams (ERDs) to map data architecture and guarantee referential integrity across all tables.
  • Designed and implemented a full relational database architecture using Oracle PL/SQL, with normalisation to 3NF and query optimisation principles.

Education

B.Sc. Computer Science
Leeds Beckett University
Sept 2023 – Sept 2027

Activities & Achievements

Volunteering
  • Acquisitions Librarian — TVS School, Madurai (2018–2020)
  • Awareness Rally Host on Cleanliness & Environmental Sustainability (2019)
  • Disaster Relief Program during 2019 Chennai Floods — led a team of over 300 people
  • Church Creative Assistant — North Church, Leeds (2024–2026)
  • Associate — The Community Grocery Store, Leeds (2026)
Leadership & Clubs
  • Lead Member — Literature Club (2017–2021)
  • Treasurer — Interact Club / Rotary Club (2019–2021)
  • Captain — Basketball Team (2015–2017)
Languages English, Tamil
Interests Keyboard & Guitar · Red Belt Taekwondo
Award Merit — Royal Australian Chemical Institute Chemistry Quiz (2020)
Training Power BI · Jira Project Management
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