Matthew Hind

JEGI LEONIS is a pre-eminent M&A advisory firm for the global technology, software, media, and business services industries. We advise founders, investors, and global corporations on a range of transactions, including buyside and sellside M&A, recapitalizations, divestitures, and debt advisory solutions. Headquartered in New York, our global team of over 80 professionals provides deep sector expertise which enhances the tailored support for each client and drives overall value. For more information, please visit www.JL-co.com.

Operational role leading Enterprise Sales and Venture Development Strategy for Modular Commerce, a B2B MarTech focused on the Retail & Apparel end market.

Market Research, with a focus on Healthcare Equities. Workshops with Investment Banks, Private Debt Funds, and Funds of Funds.

E-commerce business in the home-fitness niche - project during the first lockdown.

Organised fixtures, players and training sessions. Won the league undefeated.

A specialised study to master my skills in International Corporate Finance and Valuation. Coursework was largely dependent on one’s ability to provide strategic financial advice based on fundamental and market analysis of real business scenarios. In my thesis, I used machine learning (Using Python deployed on the UM DSRI) to predict which startups (From Crunchbase by TechCrunch) will reach an exit event (IPO or M&A) in an investor time window. The key empirical result was a successful out-prediction of industry average selection rates with the model predicting with 36.3% precision when maximising the volume of true positives. I received a grading of 95% for my thesis presentation and defence.

First-class Honours, studying Financial Economics, Corporate Finance, Quantitative Methods, Micro/Macro, Development, Environmental, Labour Economics. I graduated with a 1st in every module.