Reez Pereira

About Reez Pereira

I’m a Financial Analyst with 4+ years of experience transforming complex financial data into actionable insights that drive business performance and strategic decision-making.Currently at American Express, I focus on building data-driven financial models, analyzing large-scale transaction datasets, and improving forecasting accuracy. I’ve worked extensively with tools like Excel, SQL, Python, and Power BI to uncover revenue trends, optimize costs, and streamline reporting processes, delivering measurable impact such as improving forecast accuracy by 20% and identifying multimillion-dollar cost-saving opportunities.My background spans consulting and financial services, including experience at EY and Accenture, where I supported large-scale budgeting, forecasting, and profitability analysis across multiple business units and markets. I enjoy working at the intersection of finance and data, using analytics to solve real-world business problems and support FP & A functions.I’m particularly interested in financial modeling, data analytics, and business intelligence, and I thrive in collaborative environments where insights can influence strategic decisions.Technical skills: Excel (Advanced), SQL, Python, Power BI, TableauCore areas: Financial Planning & Analysis (FP & A), Forecasting, Budgeting, Variance Analysis, Profitability Analysis

Experience

1. Financial Analyst

   American Express

   Aug 2025 — Present

   Improved revenue forecast accuracy 20% by building financial models using historical transaction data, customer spending trends, and portfolio performance metrics evaluated through Excel, SQL, and Python.• Examined 5M+ credit card transactions using SQL and Python to identify customer spending patterns and profitability segments, enabling marketing teams to refine targeting strategies and increase campaign response rates 15%.• Decreased financial reporting cycle time 30% by automating recurring reporting workflows using Excel Power Query and Python, eliminating manual consolidation across multiple financial datasets.• Built Power BI dashboards monitoring 20+ financial KPIs, including transaction volume, portfolio profitability, and operating expenses, allowing leadership to track performance trends and identify operational changes earlier.• Discovered $1.8M cost optimization opportunities by performing variance analysis comparing actual results against budget and forecast across operational spending categories.• Assessed financial performance of new digital payment initiatives by reviewing product revenue trends and customer usage patterns, supporting leadership decisions that improved portfolio profitability 8%.

Education

• New Jersey Institute of Technology

  Masters in data science - statistics track , Data science

• DG Ruparel College of Arts, Science and Commerce

  Bachelor's of science , Statistics