• Identified digital security gaps by architecting analytics dashboards with data preprocessing techniques, structured data models, and cohort-based trend analysis
• Built and delivered end-to-end Power Apps and Power Automate solutions to streamline business processes, automate data workflows, and ensure data privacy, integrity, and accuracy
• Contributed to framework development focused on security principles, data accuracy, quality assurance, and process consistency

• Engineered, trained, and evaluated machine learning and deep neural network architectures, including CNNs, for automated bacterial spectral classification and pattern analysis
• Performed data preprocessing and dimensionality reduction using techniques including PCA, ICA, SVD, and ZCA to analyze complex spectral datasets
• Acquired and processed spectral data from bacterial colonies using Raman microscopy for molecular and compositional analysis

• Designed and implemented a robust ETL pipeline to extract, transform, and load data from multiple data sources into SSC’s primary database repository, supporting structured data integration and analysis
• Contributed to end-to-end tool development, including an HTML-based user interface and Python backend components for data parsing and acquisition
• Developed standardized Excel intake forms and data libraries used by senior business analysts, improving data consistency
• Achieved and optimized data accuracy and lineage tracking by developing a traceability system for various reports using Microsoft SharePoint Online
• Generated and produced visuals and reports in Microsoft Power BI using data from diverse sources, encompassing both local and online repositories
• Used Microsoft Power Query and Python for ETL processes to capture and manipulate data to perform advanced data modeling and predictive transformations for reports in Microsoft Power BI

• Provided one-on-one guidance to youth, fostering trust, personal development, and positive relationship building through consistent engagement
• Managed inclusive youth activities through structured planning, organization, and collaborative leadership

• Supported development of an in-house assessment product, contributing to planning, testing, and documentation
• Assisted senior business analysts in preparing requirements and assessment artifacts for data and cloud domains
• Automated retrieval of applicant data from job portals, reducing manual administrative effort

Drone Detection Models

• LightGBM and Convolutional Neural Networks (CNN) used to detect the presence of a drone through radio frequency spectral tensors

Fraud Prediction Models

• Developed predictive fraud detection models using XGBoost and Random Forest, applying ensemble learning techniques to classify fraudulent purchase transactions

Depression Prediction Ensemble

• Developed a machine learning ensemble combining Random Forest and XGboost models to predict depression risk from structured datasets

Mood Tracking Tool

• Implemented NLP-based sentiment detection using NLTK and VADER to analyze emotional patterns in user-generated text

Machine Learning (ML) & AI

Data Analytics

Programming

Behavioural Science

Tools