Logan Stuart Email and Phone Number

Experienced data analyst currently working within the consumer goods industry with a long term goal to be within the financial sector. I am passionate about data and statistics because I believe that with a complex understanding of data, many of the world's issues and hardest problems can be tackled and potentially solved. I have a mathematical and quantitative background from my studies in physics and quantitative finance, as well as my research experiences with both material science and electrical engineering. For the past several months, I have been leveraging my analytical skills at Procter & Gamble where I have done work within their Time Work Force Management Division analyzing the processes carried globally by employees within human resources and payroll in order to optimize the processes for efficiency and minimal cost. Outside of my work, I utilize my own quantimental investment strategies, investing my own personal money with a particular focus on popular stocks traded by retail investors. By analyzing a mix of company fundamentals, technical thresholds, as well as social media chatter, I have been able to ride the momentum of the so called "meme" stocks and achieve sizable returns compared to benchmarks such as the S&P 500 or Dow Jones index. Furthermore, despite the economic slump and market collapse surrounding the outbreak of Covid-19 across the world during March of 2020, I managed to earn a favorable ROI using sophisticated trading strategies, while more veteran investors connected to massive firms lost fortunes. You can read more about my insights and strategies in the journal article I co-authored, titled "Analysis of the Effect of COVID-19 on the Stock Market and Investing Strategies" (2020), published, notably, in the Center for Financial Planning Investments Ejournal and the Big Data & Innovative Financial Technologies Research Paper Series.Key Competencies:-Financial Analysis-Derivative Valuation-Risk Analysis-Financial Trend Modeling-Data Management-Task MiningTechnologies and Methodologies:Python, R, SQL, Excel, Power BI, Knime