PGPrakhar Gupta
MSc Quantitative Finance Candidate | Investment Research | Quantitative Research | Systematic Investing | Python
Newcastle Upon Tyne, UK
I am currently completing an MSc in Quantitative Finance & Risk Management at Newcastle University, building on four years of experience developing data-driven solutions for financial services at Infosys. My interests sit at the intersection of investment research, quantitative finance and technology. I enjoy applying statistical modelling, econometrics and Python to transform financial data into investment insights and systematic decision-making frameworks. Alongside my studies, I have developed systematic FX trading strategies, built reusable quantitative research infrastructure and conducted empirical research into cross-asset volatility transmission using VAR, GARCH and Diebold–Yilmaz connectedness analysis. My work combines financial theory with practical implementation through modular Python research tools. Outside academia, I actively manage a multi-asset investment portfolio across Indian and US equities, ETFs, mutual funds, cryptocurrencies and derivatives. I regularly evaluate businesses using financial statement analysis, valuation techniques and macroeconomic research, with a particular interest in identifying scalable business models and long-term investment opportunities. I am seeking opportunities in quantitative research, investment research, systematic investing, venture capital and financial technology where I can combine rigorous analytical thinking with genuine curiosity about markets and businesses.
Experience
Financial Data & Analytics Platform
Financial Data & Analytics Platform · Self-employed
Nov 2025 – Present · 8 mths
Newcastle upon Tyne, England, United Kingdom
Co-founded a quantitative research platform focused on investment research, systematic trading and financial data analytics. Built an 800+ line modular Python platform integrating Bloomberg and Yahoo Finance data for automated data collection, feature engineering, valuation analysis and portfolio analytics. Developed reusable research infrastructure supporting factor construction, backtesting, hypothesis testing and systematic strategy development across equity and FX markets. Designed scalable architecture separating data acquisition, modelling, analytics and visualisation to improve research efficiency.
Senior Systems Engineer | Infosys
Infosys Ltd · Full-time
Jun 2023 – Aug 2025 · 2 yrs 2 mths
India · Hybrid
Developed Python and C# automation solutions supporting financial reporting and enterprise analytics, reducing manual processing effort by up to 40%. Analysed more than 10 million financial records using Python and SQL while designing scalable anomaly detection and data quality frameworks. Built automated analytical workflows that reduced stakeholder review time by 30% and improved reporting consistency. Led a team of three engineers while partnering with financial services stakeholders to deliver data-driven analytical solutions.
Systems Engineer – Technology & Data Analytics
Infosys Ltd · Full-time
Jun 2021 – Jun 2023 · 2 yrs
India · Hybrid
Developed SQL data models and Power BI dashboards supporting portfolio monitoring and credit risk analytics across multiple business functions. Automated financial data extraction, transformation and validation processes across enterprise systems. Improved reporting quality through root cause analysis, data governance and analytical process optimisation.
Education
Newcastle University
MSc Quantitative Finance & Risk Management, Quantitative Finance
Sep 2025 – Aug 2026
Activities and societies: Founding Member & ESG Officer, Newcastle University Investment Fund | Bloomberg Global Trading Challenge | Quantitative Research Projects
Quantitative Finance MSc focused on systematic investing, quantitative research and financial modelling. Coursework and independent research include derivatives pricing, econometric modelling, Monte Carlo simulation, portfolio optimisation and time-series analysis using Python. Current dissertation investigates volatility spillovers across equity and digital asset markets using VAR, GARCH and Diebold–Yilmaz connectedness analysis.
DUDIT University
Bachelor of Technology, Computer Science
Aug 2017 – May 2021
Activities and societies: Capstone: Python real-time data pipeline with automated validation and modular OOP architecture.
Studied software engineering, algorithms, data structures and object-oriented programming. Developed applications in Python and C++, strengthening analytical thinking, software development and quantitative problem-solving skills.
Skills
Languages
English
Full professional proficiency
Hindi
Native or bilingual proficiency