Kuntal Gupta

Results-driven Financial Analyst and Software Developer with a strong foundation in finance, quantitative analysis, and full-stack development. Demonstrates proven expertise in financial data analytics, business intelligence, and automation using Python, SQL, and advanced Excel. Experienced in developing scalable web applications with React, Angular, and cloud platforms (AWS, Docker) to support financial reporting, risk analysis, and decision-making.

Combines technical proficiency with domain knowledge to build data-driven financial solutions and deliver actionable insights. Passionate about leveraging Generative AI and Machine Learning to modernize financial processes, enhance efficiency, and automate reporting. Adept at working across finance, technology, and business teams to drive measurable impact in fast-paced fintech, analytics, and financial environments.

Open to global opportunities in Financial Analysis, Business Analytics, Data Analytics, and select Trading and Quantitative Research positions.

Elite Trader, FundedNext, Earned top-tier trader status through comprehensive assessment of trading strategies and risk management techniques.

Finance Associate — KCL Data Science Society
Oct 2022 – May 2023

• Led financial modeling workshops on Python-based stock analysis, enhancing curriculum.
• Conducted alpha factor research using hedge fund datasets.
• Built Monte Carlo simulation models for portfolio risk demonstration.
• Increased event participation by 25% using Google Analytics-driven outreach.

Founder — Magic Table (Networking Startup)
2024 – Present

• Co-founded Magic Table, a platform connecting young professionals for curated networking dinners across major Indian cities.
• Leveraged data-driven matching algorithms to foster meaningful connections among like-minded individuals.
• Developed operational processes and digital platforms to support seamless user experience.

Part-Time Forex Trader
2021 – Present

• Independently trade global currency markets with a focus on risk management and capital preservation.
• Utilize technical analysis, market sentiment, and macroeconomic factors to generate consistent returns.
• Apply quantitative research and backtesting techniques to refine trading strategies.

• Nifty 50 Trading Strategy Research — Backtested moving averages, Bollinger Bands, RSI-based strategies, demonstrating sector-wise alpha.
• US Stocks Regression Analysis (MSc Project Leader) — Developed predictive models for portfolio management, analyzing return drivers.
• M&A Feasibility Analysis (MSc Group Project) — Evaluated potential mergers using financial and strategic data analysis.