• Transformed large, unstructured datasets into structured data for Salesforce integration, while employing PowerBI and SQL for efficient data management• Managed the end-to-end Agile development process using JIRA, ALM, TopTeam, Azure DevOps, and Visual Studio Code, resulting in improved project delivery timelines• Analyzed Salesforce workflows using Python and pandas, resulting in a 20% enhancement in lead-to-contract conversion rates• Conducted thorough requirement gathering for Sprint cycles aiming to enhance VBA-based Excel templates within Salesforce integration• Reduced number of defects found by 25% in Dev, SVT, UAT and production environments by developing troubleshooting guides and data dictionaries

• Managed a team of Diligence Data Analysts utilizing Excel, Access, VBA, Python, and SQL to enhance efficiency in preparing bulk deal acquisition data imports for Salesforce and Yardi Voyager• Applied Python and SQL for data cleansing, transformation, and automation to consequently decrease data processing time by approximately 33% for bulk deal acquisitions• Scripted stored procedures in Microsoft SQL Server in order to quickly JOIN or UPDATE datasets with different schemas.• Used VBA Macros to reconcile lease data issues before closing and prepare data uploads containing 100s of residential properties. • Developed a VBA macro-enabled Excel template enhancing data verification, ETL file generation, and SQL query creation Microsoft SQL Server users

• Presented overall performance in Power BI reports to the GA, SC, NC and TN divisions, which made up the company’s largest market share.• Developed predictive models in Python to analyze regional sales data, contributing to a strategic decision-making process that resulted in a 15% increase in land acquisition efficiency.• Created market analyses in Tableau that were used to minimize the risk of land acquisitions worth up to $20 million.• Used VBA and Macro-driven reports to translate raw Salesforce data into layman’s terms for other departments.

• Directed the management, growth, and optimization of a $2 billion portfolio of real estate assets acquired through auction, development, and merger, resulting in increased ROI and market competitiveness• Leveraged Amazon Redshift for compiling website traffic data, leading to a refined pricing strategy for rental homes and a significant boost in profitability• Enhanced portfolio profit margins by 5% annually by leveraging Spark for refining FP&A models and optimizing pricing strategies• Implemented Python and pandas analysis to calculate key performance indicators (KPI) and created a user-friendly pricing template with VBA and Excel.

• Designed and implemented a data-driven decision-making framework using Python, improving the accuracy of property valuation models by 25%.• Automated financial models with VBA Macros to price up to 60 properties per day and to update Salesforce.com with appropriate metrics.• Integrated Salesforce with internal applications to facilitate access to extensive datasets for competitive market analysis and variance reports• Used company’s acceptance criteria to build Excel-based calculators for analyzing over $1.2 billion of acquisitions within an 8-month period.