• Analyze and visualize corporate asset data using Power BI and ArcGIS, supporting the City's multi-year budget asset management plan.• Identify data gaps and assist service areas with data collection techniques, providing recommendations for process and technology improvements.• Ensure data integrity in the enterprise asset management system by collaborating with field data collectors to maintain adherence to standards and processes.

• Delivered Tier 2 frontline technical support, ensuring high-quality customer service and resolving technical issues for Corporation Staff.• Provided comprehensive technical support for software, hardware, and network issues, effectively addressing and resolving user-reported incidents.• Handled service requests such as password resets and troubleshooting, ensuring prompt and accurate responses.• Supported Council & Committee meetings by managing audiovisual services and maintaining desktop environments and associated tools.

• Developed a methodology for the archival of Encampment Data to facilitate data analysis and future reporting.• Crafted an advanced Power BI dashboard integrating data from SQL Server, Dynamics CRM, and Network Folders, aiding the city's homelessness strategy.• Established a dashboard for daily client communication and housing services data reporting for strategic executive use, significantly improving reporting time and quality, saving more than 70% of the time.• Engineered automation scripts that cut staff time by 90% for routine processes.• Spearheaded the creation of process flowcharts, digital presentations, and public informative videos using Synthesia (AI video generator), enhancing organizational efficiency and public access to information on government programs.

• Implemented an audio segmentation module within a voice cloning and translation framework, enabling its application in multi-speaker environments, thereby enabling further development of the product.• Spearheaded the initial conceptualization and design planning of the voice synthesis AI software architecture• Used Retrieval-Augmented Generation (RAG) for customizing chatbots with user data and chat history, automating prompt generation through OpenAI GPT-3.5 API, removing the need for manual prompt generation. • Assisted in the testing and review of a Large Language Model (LLM) based voice-synthesis and chat framework for text-based interactions, employing tools such as LangChain, Hugging Face, Sentence Transformers, and GPT4All, and suggested improvements.

• Made, modified, and personalized reservations for a diverse set of clients from across the globe, based on customer requirements, and abiding by the information security guidelines, with a 100% compliance rate.• Handled various tasks, focusing on precision and delivering outstanding customer service while exceeding sales targets by as much as 60%.

• Developed client-centric dashboards in Power BI for premium clients, integrating daily updates from SQL Server and Market Data API to boost engagement and investment tracking.• Implemented K-Means clustering to efficiently segment 200 clients into six categories for targeted advisor and stockbroker assignments, enhancing service delivery and reducing operational costs.• Innovated Standardized data collection forms to web-based, achieving 40% reduction in employee processing time.• Designed and deployed an automated script for daily financial reporting and alerts to the Accounting department regarding outstanding and receivable account balances, achieving a 25% improvement in operational efficiency.

• Applied Machine Learning techniques like Regression, Clustering, and Decision Trees on the given dataset of more than 200 players, and over 13 performance indicators over 15 teams, throughout the season of the tournament.• Performed Exploratory Data Analysis and Data Visualization on the data from various seasons of a sports tournament, and devised recommendations for endorsements based on the EDA of over 200,000 values of data.

• Conducted comprehensive analysis of the relationship between company stock prices and industry trends of various small, medium, and large-cap companies using NumPy, SciPy, Pandas, Matplotlib, and Sklearn over a period of 3 years, leading to actionable insights for portfolio optimization.• Successfully performed Technical Analysis using Data Visualization and Fundamental Analysis, including Beta Calculation, leveraging historical price data from over 90 Tickers. Generated accurate trade calls through Classification techniques and employed clustering to enhance portfolio diversification, resulting in reduced risk for the investor.