Tin Hang
Sales Person Online Wood Sales at Nisa's Woodshop
Elk Grove, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTin Hang is a finance-focused data scientist and sales professional with 11 years of experience blending quantitative investing, machine learning, and practical sales strategy. With a BS in Finance (minors in Risk Management & Insurance) and extensive Coursera/DataCamp credentials, Tin builds forecasting and portfolio models in Python, R, Matlab and Excel—publishing stock-focused ML code and feature engineering on GitHub. He has delivered allocation and budget analytics for government programs, managed fixed-income portfolios and traded a private book, demonstrating both institutional rigor and hands-on trading discipline. At Nisa’s Woodshop he pairs data-driven marketing and KPI analysis with customer relations, showing an unusual mix of retail sales execution and quantitative research. Persistent about education and tutoring, he mentors learners across math, coding and finance while actively exploring deep learning approaches to stock prediction.
11 years of coding experience
Deep Learning Specialization, Deep Learning, Deep Learning Specialization, Deep Learning at CourseraGeneral Education, Accountant & Mathematics, General Education, Accountant & Mathematics at Sacramento City CollegeData Scientist with Python, Data Science, Data Scientist with Python, Data Science at DataCampMachine Learning for Trading, Machine Learning for Trading at New York Institute of FinanceQuantitative Analyst with R, Quantitative Analyst, Quantitative Analyst with R, Quantitative Analyst at DatacampPython Machine Learning, Python Machine Learning at EDHEC Business SchoolCalifornia State University, Sacramento
English, american sign lanuages, Vietnamese, English
Github Skills (12)
data-visualizations10
pandas10
regression10
machine-learning10
data-visualization10
data-visualisation10
python10
data-analysis10
modeling9
statistical-models9
time-series9
finance9
Programming languages (2)
Github contributions (5)
LastAncientOne/Deep_Learning_Machine_Learning_Stock
Sep 2018 - Jan 2023
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
Role in this project:
Data Scientist
Data ScientistContributions:506 commits, 509 pushes, 1 branch in 4 years 4 months
Contributions summary:Tin contributed code related to data analysis and time series forecasting techniques for stock market data. The commits include implementations of linear regression and other statistical analysis models for predicting stock prices. The code also involves the creation of new features, such as moving averages and returns, which can be used to enhance the performance of the models.
pythonstock-analysisstock-price-predictiontensorflowstocks
LastAncientOne/LastAncientOne
Nov 2020 - Feb 2023
Contributions:286 commits, 375 pushes, 1 branch in 2 years 2 months
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