Petru Mihai

Finance Officer at A2Dominion, leveraging Python, SQL and Power BI to analyse portfolio performance, model financial scenarios, forecast revenue and assess risk. Developed analytical solutions that contributed to income increases of up to 70%. Reconciled £30m+ in monthly receipts, strengthening financial controls, identifying revenue leakage and improving reporting accuracy.

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Activities and societies: Portfolio Management Investment Management Financial Statement Analysis Ecomomics Fixed Income Equity Investments Quantitative Methods Alternative Investments Corporate Finance Derivatives

Passed CFA Level I in January 2026, demonstrating a strong foundation in investment analysis, financial statement analysis, quantitative methods, economics, equity and fixed-income valuation, derivatives, portfolio management and ethics. Developed advanced analytical and problem-solving skills applicable to asset valuation, risk assessment and investment decision-making.

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Activities and societies: Macroeconomics Economic Research Economic Analysis Financial Analysis Financial Modeling

Completed an MSc in Economics and Finance at the University of Bath, developing expertise in financial markets, investment analysis, econometrics and quantitative research. Applied statistical modelling, regression, time-series forecasting and econometric techniques to analyse economic and financial data, assess risk and support evidence-based decision-making.

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Activities and societies: Statistics Macroeconomics Econometrics Economic Research Data Analysis Economic Analysis Financial Modeling

Completed a BSc in Economics and Finance at the University of York, developing a strong foundation in microeconomics, macroeconomics, corporate finance, financial markets and econometrics. Strengthened quantitative and analytical skills through economic modelling, statistical analysis and the evaluation of financial and economic data to support informed decision-making.

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Activities and societies: Data Analysis

The Level 4 Data Analysis apprenticeship is a practical apprenticeship where I learned to work with real-world business data. Throughout the program I cleaned, manipulated, and analysed datasets, wrote SQL queries and built data visualisations and dashboards using Power BI. I also gained exposure to statistics, AI, and introductory machine learning concepts, while developing the ability to communi

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Activities and societies: Investment Management Python Machine Learning Markov Chain Analysis Lasso Regressions Markowitz Optimisation Efficient Frontier Analysis Portfolio Backtesting Monte Carlo Simulation CPPI PCA

Completed EDHEC's Introduction to Portfolio Construction and Analysis with Python, developing practical skills in portfolio optimisation, risk and return analysis, Monte Carlo simulation, CPPI strategies and portfolio backtesting. Applied quantitative techniques including Markowitz optimisation, efficient frontiers, factor models and statistical analysis to investment decision-making.

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Activities and societies: Data Analysis Complex Problem Solving Data Lakes Performance Tuning Data Warehousing Data Quality Descriptive Statistics Data Pipelines Data Presentation

Completed a comprehensive SQL course, developing practical skills in relational database analysis using JOINs, subqueries, CASE expressions, aggregate functions and views. Applied SQLite and DBeaver to extract, transform and analyse multiple datasets, performing exploratory analysis, calculating key metrics and generating actionable insights through a hands-on project.

Grade: N/A

Activities and societies: Financial Statement Modeling Financial & Valuation Modeling DCF Modeling Leveraged Buyout Modeling M&A Modeling Trading Comparables Transaction Comparables Valuation 3-Statement Modeling

Completed Wall Street Prep's Financial & Valuation Modeling course, developing practical skills in integrated three-statement modelling, financial forecasting, DCF valuation, comparable company and precedent transaction analysis. Applied techniques including WACC, terminal value calculations, sensitivity analysis, EBITDA adjustments and M&A accretion/dilution modelling.