Currently a full-time student at Columbia University pursuing a Master's degree in Operations Research and will graduate in Dec 2024. Graduated from the University of California, Santa Barbara majoring in Statistics and Data Science, minoring in Applied Psychology. Currently looking for jobs in data analytics/business analytics/data science/machine learning engineer. Multiple internship experiences in data analysis, business analysis, data pre-training, machine learning, ELT pipeline development, data modeling, data warehousing. Proficient in independent thinking, strong self-motivation, cross-functional communication, problem solving, fast learning, managing multiple tasks.Technical Skills: Proficient in Python, SQL, and R for data modeling, analysis, and machine learning.Data Platforms: Experienced with Snowflake, PostgreSQL, and BigQuery for data warehousing.ETL/ELT Tools: Strong experience with Fivetran, dbt, and Snowflake for data integration.Majoring in Statistics and Data Science during my undergrad, and acquiring internships in the diverse domains of business, such as technology, advertising, consulting, and plenty of research projects that reinforced my programming skills through diversified real-life topics, I am armed with solid quantitative thinking and tools to optimize operations and management. Therefore, I am prepared to meet more challenges now. I am now looking to bring my expertise to a forward-thinking organization where I can continue to develop my skills and make data-driven decisions that contribute to business growth. Let’s connect to discuss how I can add value to your team!It would be delighted to hear from you, feel free to drop me a message anytime or email me at: yh3655@columbia.edu
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Machine Learning Intern, Ict Team-Antenna GroupHuawei Jul 2024 - Sep 2024Shanghai, China• Simulated station channel data as two-channel computer vision image data and implemented Deep Neural Network-Vision Transformer (ViT) model pretraining using torch, predicting unknown transmission time intervals (TTI) with a training set of 10,000 data samples and 1,000 epochs, achieving a loss below 0.2 • Built a Mask Auto-Encoder model using deep learning to perform time/frequency dual-dimension frequency hopping sampling, reducing encoder computation by 75% and achieving a loss as low as 0.06• Finetuned a ViT model with over 600 million parameters, improving the alignment between the generated data and the original Power Delay Profile (PDP) visualization -
Strategic Analyst InternShenzhen Rabbitpre Intelligent Technology Co., Ltd. Jun 2023 - Aug 2023Beijing, China• Applied Python with ‘selenium.webdriver’ to scrape over 1000 records per category of women's fashion e-commercedata from 'Chanmama' website; employed Tableau to visualize product revenue, growth trends, market size• Scraped data for 5000+ ‘Gorpcore’ style products, leveraged Python’s ‘wordcloud’ and ‘jieba’ for high-frequencykeyword extraction for word cloud graph to depict consumer preferences within the ‘Gorpcore’ trend• Produced a map to picture regional customer distribution of dress purchases deploying color gradients to indicatedensity; resulting in an 8% click through rate• Compiled and released the ‘2023 Women's TikTok E-commerce Report’, segmenting insights into market trends,customers regional spread/TikTok influencers/e-stores market performances, garnered 300+ views in two months -
Business Analyst InternCapgemini Jul 2022 - Sep 2022Shanghai, China• Utilized ‘pdfplumber’ in Python to collect data on graduate employment quality reports from all universities withinPearl River Delta Zone for year 2021 into Excel, increasing the efficiency of data collection by 2 days• Derived key economic indicators for cities within the Pearl River Delta, such as GDP, per capita disposable income;performed correlation studies of these indicators with graduate employment data through Python• Designed and published graduate employment satisfaction survey, obtaining 1114 responses; executed a detailedvisual analysis of sample geographical distribution, and statistics as a comparison to real graduate employment data -
Analyst Assistant InternTapjoy (Acquired By Ironsource) Jul 2020 - Sep 2020Beijing, China• Conducted A/B testing to optimize displayed advertising contents, identified and replaced creatives that yielded higher conversion rates, resulting in a 3% overall increase in conversion rates for Lillith Games Company for current quarter• Confirmed reliability and integrity of in-game incentives system by testing games and extracting back-end data toensure correct allocation of credits to players’ accounts via the Offerwall• Leveraged MicroStrategy to obtain time series data and visualized the conversion rates and revenue growth of clientcompany, accomplishing a 70% accuracy rate in revenue growth prediction
Yueting(Rita) Han Education Details
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Operations Research -
Statistics And Data Science
Frequently Asked Questions about Yueting(Rita) Han
What is Yueting(Rita) Han's role at the current company?
Yueting(Rita) Han's current role is MS Operations Research @ Columbia University '25 I Statistics&Data Science @ UCSB '23 | Data & Analytics Expert | Machine Learning Enthusiast.
What schools did Yueting(Rita) Han attend?
Yueting(Rita) Han attended Columbia University, Uc Santa Barbara.
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