Headline

Quantitative Research Analyst | Industrial Engineer | MSc Finance @ Cranfield

About

I connect market data to investment decisions through equity research and quantitative analysis. At Cranfield, my research centres on constructing a UK Fear and Greed Index for the FTSE 100, validated against Brexit, COVID-19, and the 2022 UK mini-budget. I am testing its predictive power for FTSE 100 returns, estimating sentiment betas for individual constituents, and building factor-model portfolios to assess risk-adjusted returns. I have also constructed sterling bond portfolios benchmarked against the Bloomberg Barclays UK Aggregate, hedged with gilt futures, and conducted panel studies on international bank risk and profitability across more than 5,500 bank-year observations. Prior to Cranfield, I worked on financial modelling in capital-intensive environments, including cost control on renewable energy projects at Tata Power Solar and working capital optimisation at a research chemicals firm. That background underpins the precision I bring to valuation and research work.

Location

United States

AI stack

anthropic apis

claude code

claude

github copilot

grok

Work experience

Quantitative Research Analyst at Summer Atlantic Capital, Aug 2026 - Present · 4 mos, Newark, DE

Quantitative Research Analyst Intern at Summer Atlantic Capital, Jun 2026 - Aug 2026 · 3 mos, Newark, DE

Finance & Strategy Consultant at Supreme Scientifics, Jun 2024 - Jul 2025 · 1 yr 2 mos, Bangalore Urban, Built Python and Excel forecasting models achieving 92% accuracy, improving working capital efficiency by 15% by aligning procurement cycles directly with cash flow movements. Analysed and managed ~£200k in annual procurement spend, maintaining a 95% fulfilment rate through data-driven vendor planning and inventory optimisation. Negotiated supplier contracts totalling ~£500k annually, securing 45-day credit terms and reducing lead times from 14 to 9 days through KPI-driven vendor performance tracking.

Supply chain and finance Intern at Tata Power Solar Systems Limited, Aug 2023 - Sep 2023 · 2 mos, Bengaluru, Applied Python and Excel-based predictive models to cost tracking across renewable energy projects exceeding ₹160Cr, improving forecast accuracy by 12.5%. Conducted variance analysis on supplier quotations and purchase orders, identifying cost inefficiencies and standardising financial evaluation criteria across regional offices. Delivered a data-driven cost and risk mitigation report to senior management that was subsequently integrated into Tata Power Solar's corporate budgeting framework.

Education

Master of Science - MS, Finance, Cranfield School of Management

Bachelor of Engineering - BE, Industrial Engineering and Management, B. M. S. College of Engineering