• Performed monthly general ledger reconciliations and managed accounting activities, including payroll processing and month-end close reviews to ensure accurate reporting, grant compliance and donor transparency• Collaborated with program managers to conduct variance analysis between actual and forecasted data, optimized budget reallocations and improved alignment with funding requirements and program goals by 12% in QuickBooks• Developed revenue and expense tracking models for operational activities, leveraging Excel to monitor financial performance across 3+ programs, contributing to 10% increase in overall efficiency in grant utilization and budgeting• Conducted trending analysis on fund utilization and grant expenditure compliance, utilizing Excel (XLOOKUP, pivot tables) to streamline reporting and reduce 15% allocation errors, ensuring grant and donor compliance• Designed dashboards in Tableau to visualize funding allocation and project expenditure trends; identified under-utilized resources and areas of overspending to improve fiscal stewardship and optimize resource distribution

•Automated data collection using Python (Beautiful Soup) to scrape 71.8K row medicine, and enhanced data accuracy by 20% through SQL and Python preprocessing, including merging, handling nulls, duplicates, and text normalization• Generated 58.1K Q&A pairs from structured data using Python and transformed Q&A pairs into vectors using Word2Vec, then stored them to Pinecone for LLM training, finalizing data transformation of medicine pipeline with NLP process

• Analyzed revenue and cost data from annual report of leading apparel brand, leveraging financial models to assess the feasibility of a 3-year strategic plan aimed at increasing market share and optimizing production costs• Executed comprehensive market research on fashion retail using Bloomberg, analyzing demand trends, consumer preferences and competitive positioning to assess industry opportunities and risks • Created 5-year revenue projections for 3 product lines and presented insights based on public data and presented findings using Power BI, supporting the evaluation of the brand’s potential market entry strategy• Collaborated with teams to evaluate investment, applying scenario analysis and stress testing to refine financial model and deliver forecasts that improved risk-adjusted decision-making and increased model accuracy by 8%

• Prepared monthly revenue projections for financial product contracts by collaborating with cross-functional teams to collect data and aligning contract performance with revenue objectives through discussions with sales team• Reconciled revenue data in SAP with client sales reports and contract agreements to ensure accurate revenue reporting; Applied adjustments, including reclassifications and accruals, to maintain precise financial records• Investigated client portfolios return variances with sales managers to identify causes such as client turnover and investment patterns changes. Incorporated financial estimations into Excel-based forecasts improving precision of financial projections based on the latest client activities by 11%• Conducted ad-hoc analysis of client data to identify growth opportunities within client financial portfolio; Suggested revenue- boosting strategies, presented to sales team to enhance client engagement and sales efforts