I help organizations improve financial visibility, forecasting accuracy, and business decision-making through budgeting, variance analysis, financial modeling, dashboards, and automation.
Financial Analyst with 5+ years of experience in FP&A, budgeting, forecasting, financial modeling, and variance analysis. I enjoy turning complex financial and operational data into clear insights that support strategic decisions.
My background spans financial reporting, portfolio valuation, forecasting, cost analysis, dashboard creation, and process improvement. I have worked across banking, startup, consulting, and analytics-focused roles, using tools such as Excel, SQL, Tableau, Power BI, Python, SAP, and Oracle ERP.
A blend of finance, analytics, reporting, and business problem-solving skills built across cross-functional roles.
These projects highlight a mix of financial analysis, automation, valuation, and predictive analytics.
Tracked financial performance across portfolios and improved reporting visibility for decision-makers.
Supported budget vs actual tracking and variance analysis for high-value portfolios, improving financial accuracy and transparency. This work helped reduce reporting discrepancies by 25%.
Automated recurring reporting workflows to reduce manual effort and improve accessibility.
Built automated dashboards using Tableau and Python, reducing manual effort by 30% and improving data accessibility for finance and business teams.
Developed forecasting models to support planning and identify cost-saving opportunities.
Developed and maintained financial models for budgeting, monthly and quarterly forecasting, and scenario analysis, contributing to a 15% reduction in operating costs.
Delivered accurate valuation reporting under tight deadlines for investment portfolios.
Managed tax lot reporting and valuations for portfolios ranging from $5M to $50M while maintaining 99%+ accuracy and supporting financial reporting compliance.
Machine learning capstone built on a 24M-row dataset for sneaker price prediction.
Built predictive models using Python and Tableau, achieving 88.12% accuracy for selected product segments and improving business decision-making efficiency by 10%.
Large-scale analytics project focused on data quality, trends, and financial outcome prediction.
Conducted exploratory analysis on a 982,698-entry healthcare dataset and used machine learning models to predict financial outcomes with an R² value of 0.970.
Download my latest resume for a detailed overview of experience, achievements, technical skills, and education.
I’m open to Financial Analyst, FP&A, business analytics, and data-driven finance opportunities.
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