Industry

Some of my professional experience includes:

Foresight Group LLP – 2019-2019

Private Equity Intern
  • Developed a Python based tool to interactively assess different investment environments, which was subsequently adopted by the business.
  • Designed and implemented a Deep Learning model (PyTorch, NetworkX) to determine the optimal locations for UK battery facilities.
  • Responsible for the financial modelling and financial due diligence of 1 acquisition (£250Mn+) and subsequent restructuring.
  • Facilitated communication between vendors and operational due diligence team, managing information flow.
  • Collaborated directly with fund principle to craft pitch-books for potential investors and managed accounts.

Foresight Group LLP – 2018-2018

Private Equity Intern
  • Screened potential investment targets from a financial and operational perspective, presenting findings to the Investment Committee.
  • Conducted valuations using private entity data, precedent transaction metrics and DCF methodology.
  • Managed the data room, coordinating financial & technical due diligence for 2 acquisitions (£500Mn+).
  • Maintained Investment pipeline databases for multiple portfolios across different geographies.

OSTC Group – 2015-2016

Proprietary Trader
  • Formulated and implemented a market view based on statistical and technical analyses, operational knowledge and market dynamics.
  • Utilized Python (NumPy, SciPy, SKLearn, NetworkX, SQLite) to build data analytics tools based on Granger Causality.
  • Responsible for the full life cycle of trading strategy development, holding direct P&L and operational accountability for trading book.
  • Worked both independently and within a small team in a dynamic, research-oriented environment.

Academia & Teaching

Some of my academic experience includes:

Durham University – 2017-Present

Module Leader
  • Machine Learning for Finance (MSc Finance) 2020/2021 - Pandas, NumPy, SciPy, PyTorch, Plotly - Due to the popular demand of the previous year, this course has been offered to MSc Finance students in the Easter term.
  • Machine Learning for Finance (MSc Finance) 2019/2020 - Pandas, NumPy, SciPy, PyTorch, Plotly - With a colleague, I designed and delivered an optional module to the MSc Finance cohort, which was oversubscribed by 600 applicants.
Graduate Instructor
  • Real Estate Finance (BSc Economics & Finance) 2020/2021 - An introduction to evaluation methods of Real Estate assets - Instructor (100 Students).
  • Foundations of Finance (BSc Economics & Finance) 2020/2021 - An introduction to the evaluation of financial assets - Instructor (400 Students).
  • Financial Modelling & Business Forecasting (MSc Finance) 2019/2020 - Time Series Econometrics - Instructor (400 Students).
  • Financial Markets & Institutions (BSc Economics) 2018/2019 - Trading venues & Financial Instruments - Instructor (320 Students).
  • Fundamentals of Finance (BSc Finance) 2017/2018 - Introductory Finance - Instructor (340 Students).