Financial analyst, Analyst

Abhilash Gangineni

TX 817-***-****

www.linkedin.com/in/acg-fin/ *************************@*****.*** PROFESSIONAL PROFILE

Master of Science in Finance candidate with a background in computer science, specializing in financial analysis, data modeling, and investment strategy. Skilled in leveraging technical expertise to drive data-driven financial decisions, optimize portfolios, and enhance risk management. Seeking a finance role to apply analytical and quantitative skills in strategic decision-making. CORE COMPETENCIES

Financial Analysis Customer Service Risk Assessment Team Collaboration Communication Problem Solving Organizational Skills Time Management Investment Strategy Risk Management Portfolio Optimization Market Research Data Modeling Quantitative Analysis Forecasting Trading Strategies Financial Modeling TECHNICAL SKILLS

Software: Python, MySQL, MS Excel (advanced), Power BI. Tools: Bloomberg Terminal, S&P Capital IQ Pro, MSCI. Certifications: Bloomberg Finance Fundamentals, Bloomberg Market Concepts, Bloomberg ESG. Apr 2024 EDUCATION

Master of Science in Finance GPA: - 3.66

University of North Texas, Denton, TX

Bachelor in Computer Science Engineering

Vellore Institute of Technology, Amaravati, India

Work Experience

TRADESHALA Jan 2022 – Dec 2023

Capital Market Trainee Bengaluru, India

• Conducted comprehensive scenario generation and rigorous stress testing of market strategies, successfully identifying 15 potential risks and developing targeted mitigation strategies that improved overall strategy resilience by 30%.

• Executed detailed stress testing on 5 key market strategies, identifying critical vulnerabilities and implementing 7 targeted risk mitigation strategies; resulted in a significant enhancement of long-term strategy reliability and stakeholder confidence.

• This developed a trading strategy that resulted in a 15% increase in portfolio returns over six months.

• We interpreted market trends and applied quantitative methods to optimize portfolio performance, leading to a 10% reduction in portfolio risk.

Project Experience

Advanced Portfolio Optimization Using Python Dec 2022 - Jun 2023

• Designed a Python-based portfolio optimization model, improving the return-to-risk ratio by 25% through volatility reduction and optimized asset allocation.

• Analysed 1,000+ historical data points across 10 asset classes to calculate efficient frontiers using Modern Portfolio Theory

(MPT).

• Applied constraints to limit sector exposure to 30% and individual asset weights to 15%.

• Created a Power BI dashboard to visualize metrics, showing a 22% Sharpe ratio improvement and a 35% reduction in downside risk.

• Back tested the model with 5 years of historical data, achieving a 20% higher cumulative return compared to equal-weight strategies.

LEADERSHIP, CAMPUS & COMMUNITY INVOLVEMENT

UNT Financial Management Association – Member Jan 2024 – Feb2025 VIT-AP, Sports Club – Vice President Jan 2021 – May 2022 VIT-AP, Run 4 a Cause Club – Board Member Dec 2020 – Jan 2022

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