
Detail-oriented IT professional with 4 years of experience in job scheduling, monitoring, and creation using tools such as Control-M, Autosys, CA-7, Mainframe, Zeke, and Tidal. Proven ability to manage and disconnect logical cross-connections within multiplexers across various bandwidths. Skilled in layer 1 activities of the OSI model, ensuring seamless operations in network and infrastructure environments. Highly adept at optimizing workflows and troubleshooting issues to maintain high system reliability.
Authored a detailed "Security Assessment Protocol" for CAO of WNY, Inc., encompassing Physical Security, IT Security, and Data Privacy. Defined assessment methodologies, identified evaluation criteria for physical access controls, IT assets, and network security, and ensured alignment with privacy regulations such as GDPR and HIPAA. The policy provided a structured framework for comprehensive security assessments.
Title: Querying Multiple Features of Groups in Relational Databases
This project addresses challenges in expressing complex aggregate and grouping queries in SQL, proposing an extended SQL syntax to manage these issues efficiently. It introduces a new relational algebra operation for multi-level aggregation and provides a translation from the extended SQL language. The goal is to simplify the representation of queries involving repeated selections, grouping, and aggregation while improving execution efficiency in database systems
Tools: Python
Title: NYC Real Estate Price Prediction Project
Developed a machine learning solution to predict real estate prices in NYC using the Kaggle dataset. Conducted data preprocessing, exploratory data analysis, and implemented various models, including KNN, Decision Trees, Random Forest, XGBoost, and SVC. Applied hyperparameter tuning, feature engineering, and optimization techniques to improve model accuracy.
Tools & Techniques: Python, Scikit-learn, Pandas, NumPy, Random Forest, XGBoost, SVC.