• Quantitative and Technical Analysis: Utilized statistical analysis, quantitative modeling, and various financial theories (e.g., Black-Scholes, Binomial Option Pricing) to interpret market data and develop robust trading models and strategies.• Algorithmic Trading: Led the implementation of advanced algorithmic trading techniques using libraries such as Python, TensorFlow, and QuantLib, optimizing market entry and exit points for high-frequency transactions.• Macro Trading: Applied a deep understanding of global economic indicators and macroeconomic trends to inform strategic trading decisions.• Risk Management: Employed dynamic risk management methodologies (e.g., VaR, ES, Stress Testing) to ensure effective capital preservation and minimize potential losses.• Cross-Functional Collaboration: Worked with developers and analysts to integrate algorithmic trading strategies seamlessly within the organization.• Continuous Learning: Stayed ahead of industry advancements by continuously learning and adapting strategies to align with emerging market dynamics.• Mean Reversion Strategies: Spearheaded advanced mean reversion strategies, enhancing trading performance by capitalizing on market inefficiencies through quantitative analysis.• Automation Solutions: Pioneered automation solutions for trade execution, reducing latency and enhancing overall trading efficiency through advanced quantitative techniques.• Market Tools: Proficient in Bloomberg Terminal, Yahoo Finance, and other market tools for comprehensive financial data analysis and market monitoring.

• Investments Strategy Development: Generated new investment ideas and actionable strategies using quantitative and technical analysis tools (e.g., Monte Carlo Simulation, Portfolio Theory).• Global Macro Analysis: Integrated macroeconomic indicators, geopolitical events, and central bank policies into investment decision-making processes.• Portfolio Management: Managed equity trading portfolios with a focus on optimizing performance through data-driven strategies.• Financial Economics: Applied financial economics principles, including monetary policy and interest rates, in trading strategies.• Machine Learning Applications: Utilized machine learning models (e.g., Logistic Regression, Random Forest) for predictive analysis and strategy development.

• Financial Data Analysis: Analyzed financial data, performed cost analysis, and assessed financial statements to support decision-making processes.• Budgeting and Forecasting: Prepared budgets, financial forecasts, and monitored targets for effective financial management.• Administrative Support: Provided administrative support, including schedule management, meeting coordination, and documentation handling.• Data Management: Utilized Excel for data analysis, modeling, and reporting. Ensured compliance with regulations in financial reporting.• Time Series Models: Applied time series models (e.g., ARIMA, GARCH) for financial forecasting and trend analysis.