Dhaarani Singaravel

Software Developer @Tracerent

Vancouver, BC, CA

Collaborate with a lean agile team to build a dynamic revenue management software tailored for multi-family property management, enabling optimized rent pricing through predictive modeling to reduce vacancies and maximize revenue. Google Drive Integration: Designed and implemented the initial version (V0) of an automated pipeline to ingest monthly client data from Google Drive into the database using Python and the Google Drive API, enabling seamless forecasting model input. Google Maps API Integration: Developed the initial version (V0) of a custom integration to retrieve proximity-based location data across 20 parameters, enhancing model inputs. Conducted API cost analysis and optimization to minimize usage and reduce operational expenses—crucial for a resource-conscious startup. Restructured and optimized the Silver-tier database architecture to improve performance, enforce data integrity, and streamline access across the data pipeline. Design and maintain ETL translation scripts to automate the transformation of diverse client datasets across data layers, ensuring seamless integration into the predictive model pipeline. Model Fine-Tuning: Customize and fine-tune the predictive pricing model per client to adapt to individual data behaviors, improving the relevance and accuracy of pricing recommendations. Conduct in-depth rent recommendation analysis, identifying patterns and refining model outputs for actionable insights. Utilize Playwright and UiPath RPA bots to automate large-scale web scraping processes for extracting government resource data, as well as real-time property and rental market information, supporting data-driven decision-making and model inputs.Tech Stack: Python (Pandas, NumPy), MySQL, AWS, GCP, Playwright, GitHub, JIRA