Machine Learning Engineer
Current• Created aggregated dataset from scraping real-time data sources. Built daily data pipeline jobs.• Improved decision-making for players during drafting phase in Dota 2 matches.
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Jeffrey Kuo is listed as Machine Learning Engineer at Self-employed, based in Saratoga, California, United States. AeroLeads shows a work email signal at hl.com and a matched LinkedIn profile for Jeffrey Kuo.
Jeffrey Kuo previously worked as Masters Student at University Of California, Berkeley and Competitive Dota 2 Player at Self-Employed. Jeffrey Kuo holds Master Of Arts - Ma, Statistics, 3.95 from University Of California, Berkeley.
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I recently graduated from UC Berkeley's Master's of Statistics program in 2023 and I'm currently seeking Data Science and Data Analyst roles. My coursework included: Machine Learning, Statistical Computing, Probability, Statistics, and Linear Models. I executed on 3 major projects during my time: Deep Learning Model for Audio Classification, Estimating Probabilities of Meter Violation Citation in San Francisco, and Predicting Outcomes of NBA Games. Completing this rigorous program solidified my determination to pursue a career in data science and analytics. Prior to entering my Master's program, I worked for over 2 years in investment banking solving complex problems with data-driven analyses. I built detailed financial models and conducted analyses in Excel. I communicated my analyses by writing reports, creating visualizations, and presenting to senior leaders. I delivered on several projects to completion and collaborated across teams and external partners to achieve shared goals. I proved I could quickly learn and adapt in a high-stress, fast-paced environment. I particularly enjoyed the aspect of extracting, aggregating, and analyzing data across various sources to drive my overall analysis.Following that, I pursued a career in my longtime passion of competitive Dota 2. I achieved a top 40 ranking across North and South America in 2020. Although I did not attain my ultimate goal of playing in TI, I'm satisfied with having given it a shot. I gained valuable experience in a highly entrepreneurial, team-oriented environment.
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• Created aggregated dataset from scraping real-time data sources. Built daily data pipeline jobs.• Improved decision-making for players during drafting phase in Dota 2 matches.
Projects: Deep Learning Model for Audio Classification• Developed a CNN for genre classification of audio using transfer learning with a pre-trained model, and further improved performance by adding 3 layers, implementing batch training, and fine-tuned model on FMA audio dataset.• Trained music genre classification models on features extracted by pre-trained CNN. Improved accuracy over baseline models by 8 percentage points.Estimating Probabilities of Meter Violation Citation in San Francisco• Developed a statistical model under a probability theory framework to estimate probabilities of getting a citation for meter violation in San Francisco by street section, day of week, and time of day.• Conducted exploratory data analysis to identify patterns and trends in dataset to segment analysis by time and location.Predicting the Outcomes of NBA Games• Developed logistic regression models for predicting outcomes of NBA regular season games in 2022-2023 by training on past games using differences in moving averages of recent team statistics as covariates. Achieved accuracy of 71 percent.Relevant Coursework: Modern Statistical Prediction and Machine Learning, Intro to Statistical Computing, Intro to Probability at an Advanced Level, Intro to Statistics at an Advanced Level, Linear Models, Capstone Project
• Pursued a professional career in esports as a competitive Dota 2 player from 2018-2020. • Achieved top 40 (0.002%) in solo matchmaking ranking across North and South America.• Placed 4th and 2nd respectively at WESG US regionals in 2018 and 2019.
Los Angeles
• Resolved client companies’ valuation disputes through financial modeling in Excel using discounted cash flow, public comparable companies, precedent transactions, and other ad hoc analyses.• Communicated complex technical analyses to a wide variety of audiences through Excel and PowerPoint visualizations, verbal presentations, and writing.• Worked closely with everyone ranging from interns to managing directors to lawyers on internal and external teams to build cases for our clients.• Enjoyed working with company, market, and industry data I extracted from Capital IQ, Bloomberg Terminal, and analyst reports to draw insights and drive my analyses.• Selected Project Experience: o [$100 million - $300 million] Valuation of Solar Cell Manufacturer Joint Venture Company Resolved dispute between 2 companies in arbitration by deriving fair value of joint venture company using multiple scenarios liquidation analyses across 4 valuation dates. Built out 3 statement financial model for 5 projected years. o [$1 billion] Valuation of Onshore and Offshore Drilling Company Attained a 20% higher share price for minority shareholders by producing compelling valuation analyses in the scope of a management buyout dispute case. o Goodwill Impairment Analysis of a Waste Services Company Passed testing for client by showing no impairment in any of the 8 reporting units, the rest of the company, and any intangible assets using DCF, comparable companies, and precedent transactions methodologies.
Los Angeles, California, United States
• Ensured quality of our team’s models by reviewing for mathematical and logical accuracy and presenting findings.• Provided background literature and support for expert reports by researching and citing academic papers.
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Jeffrey Kuo works for Self-employed.
Jeffrey Kuo is listed as Machine Learning Engineer at Self-employed.
AeroLeads has found 1 work email signal at @hl.com for Jeffrey Kuo at Self-employed.
Jeffrey Kuo is based in Saratoga, California, United States while working with Self-employed.
Jeffrey Kuo has worked for Self-Employed, University Of California, Berkeley, and Houlihan Lokey.
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Jeffrey Kuo holds Master Of Arts - Ma, Statistics, 3.95 from University Of California, Berkeley.
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