Financial Analyst with practical experience in financial modeling, valuation (DCF & Multiples), budgeting, forecasting, and KPI reporting. Strong focus on real estate finance, strategic planning, and data-driven business decisions.
M.Sc. in Business Administration (2022–2025) – GPA 2.1/1.0 Diploma Transcript
Coursework: Corporate Finance, Corporate Valuation and Financial Modelling, IFRS, Applied Econometrics, Strategic Management & Marketing.
Master Thesis: "How AI Learns from Social Media Data to Influence Consumer Behavior"
Bachelor in Economics (2017–2021) – Diploma with Honors – GPA 4.5/5.0 Diploma Transcript
Coursework: Time-Series Analysis, Econometrics, World Economy, Finance and Credit, Accounting.
Bachelor Thesis: "Predictability of American Companies’ Shares Expected Profit"
DCF & Multiples Valuation | View on GitHub | Final Report
• Built a full 3-statement financial forecast and performed Discounted Cash Flow (DCF) and Multiples valuation of Emaar Properties PJSC.
• Conducted peer benchmarking, scenario analysis (optimistic, base, worst), and delivered an investor-ready valuation report.
Corporate Budgeting & Forecasting | View on GitHub | Final Report
• Developed a complete budgeting, forecasting, and cash flow management model for a fictional property flipping startup.
• Built revenue and cost models, break-even analysis, CapEx and working capital plans, KPI dashboards (burn rate, runway, ROI), and prepared an investor-grade report
Scoring Model & Report | View on GitHub | Final Report
• Conducted full credit risk evaluation across Emaar, SABIC, STC, Emirates NBD, and Ooredoo.
• Built a financial ratio-based scoring model and qualitative assessment framework to produce internal risk ratings.
• Analyzed liquidity, leverage, profitability, efficiency, and macro-sector exposures for each company.
• Developed strategic lending recommendations and risk mitigation structures tailored to each corporate entity.
• Produced a professional report replicating real-world credit analyst work for investment and lending decisions.
Machine Learning (LogReg & Random Forest) | View on GitHub | Final Report
• Built an automated credit scoring model using real consumer lending data to predict Probability of Default.
• Applied data cleaning, feature engineering, and class imbalance handling.
• Trained and evaluated Logistic Regression and Random Forest models; achieved strong AUC-ROC scores.
• Segmented applicants into five risk bands (A-E) enabling data-driven lending decisions.
• Delivered full visual report with interpreted charts and business risk strategy recommendations.
Private Equity Acquisition Model & Report | View on GitHub | Final Report
• Built a full private equity acquisition model for an 80% stake in a Dubai-based real estate services firm.
• Forecasted 5-year financial performance (Revenue, EBITDA, Net Income) and exit valuation under multiple scenarios.
• Calculated base-case IRR of 15.5% and MOIC of 2.05x through dynamic cash flow and exit modeling.
• Conducted sensitivity analysis to assess impact of exit multiples on projected returns.
• Delivered an investment report, Excel valuation model, and 1-page visual executive summary.
Business Analysis & Tableau | View on GitHub | Final Report | Presentation
• Conducted full-cycle data cleaning, exploratory data analysis (EDA), and KPI assessment on sales, customer, and inventory data using Python,Excel, and Tableau.
• Identified profit leaks, loss-making sub-categories, and regional performance disparities across retail operations (~$2.3M in gross revenue analyzed).
• Built an interactive Tableau dashboard enabling dynamic filtering by region, product, and discount rates for executive decision-making.
• Delivered data-driven recommendations to optimize pricing strategies, promote top-seller categories and identify cap discounts.
• Prepared a complete Business Report and Analytical Summary for stakeholder presentation.
Business Analysis & draw.io | View on GitHub | Final Report | Presentation
• Led a business process improvement project for a simulated telecom company to optimize customer support ticket handling, targeting a 40% reduction in resolution time and 50% decrease in escalations.
• Conducted stakeholder analysis, mapped AS-IS and TO-BE workflows using draw.io, and prepared a Business Report with functional and non-functional specifications.
• Designed KPI framework tracking resolution time, Customer Satisfaction (CSAT), Service-Level Agreement (SLA) compliance, and ticket routing accuracy.
• Delivered a comprehensive solution recommendation including smart ticket triage, SLA automation, chatbot handling of tier-1 issues, and dashboard reporting.
• Prepared executive-style documentation and presentation showcasing business impact.
📍 Berlin, Germany
📱 +49 174 490 7680
Want the Russian or German version? Use the links at the top ↑