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AI summary
Progress on portfolio tracking includes various completed projects in economics, stock markets, machine learning, and collaborative projects. Key portfolio projects focus on financial forecasting, liquidity analysis, credit risk prediction, investment optimization, sales analysis, and automated reporting, utilizing tools like Python, SQL, Power BI, and Tableau.
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In progress
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Fork Repo
Private Repo
5-Advanced Excel
MyCollaborative Projects
Portfolio Projects for a Financial Data Analyst Role
1. Financial Forecasting & Variance Analysis (Python, SQL, Power BI)
- Built a financial forecasting model to predict revenue and expenses using historical data.
- Conducted variance analysis to compare budgeted vs. actual financials, identifying key drivers of discrepancies.
- Leveraged SQL queries to extract and clean financial data from a relational database.
- Created an interactive Power BI dashboard for real-time tracking of financial performance.
2. Treasury & Liquidity Analysis (SQL, Python, Excel)
- Developed an automated liquidity monitoring system to track cash flows and working capital trends.
- Designed a SQL-based cash flow forecasting tool that improved liquidity planning efficiency.
- Applied Python (Pandas & NumPy) for time-series analysis to model future cash reserves.
- Utilized Excel for dynamic scenario analysis, stress testing, and funding gap identification.
3. Credit Risk Analysis & Loan Default Prediction (Machine Learning)
- Built a classification model using logistic regression & XGBoost to predict loan defaults.
- Analyzed customer credit history, income, and financial ratios to determine risk exposure.
- Applied feature engineering techniques (one-hot encoding, scaling) for model optimization.
- Evaluated model performance using ROC-AUC, precision-recall metrics, and cross-validation.
4. Investment Portfolio Optimization (Python, Monte Carlo Simulation)
- Designed an asset allocation model to maximize returns while minimizing risk.
- Used Monte Carlo simulations and the Sharpe ratio to optimize a diversified investment portfolio.
- Applied Markowitz’s Modern Portfolio Theory (MPT) to determine efficient frontier allocations.
- Visualized investment performance trends using Matplotlib & Seaborn.
5. Superstore Sales & Profitability Analysis (SQL, Python, Tableau)
- Analyzed transaction-level sales data from a retail superstore to identify profit drivers.
- Designed SQL queries to extract KPIs (customer retention, average order value, discount impact).
- Used Pandas & Matplotlib for EDA, finding patterns in high-value vs. low-value customers.
- Built a Tableau dashboard for executives to monitor profitability trends and growth opportunities.
6. Automated Financial Reporting (Python, Excel, VBA)
- Developed a Python script to automate the generation of monthly financial statements.
- Integrated Excel VBA macros to streamline reconciliation and data validation tasks.
- Created pivot tables and Power Query transformations for structured reporting.
- Reduced manual effort in financial reporting by 50%, improving efficiency.