Han Gao
Data Science Intern @CBRE Investment Management
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WORK HISTORY
Data Science Intern @CBRE Investment Management
Dallas, TX, US
Built an AI-powered newsletter pipeline (Google Search API + LangChain) with prompt engineering- Modeled real estate market dynamics, integrating macro/microeconomic data, LLM-extracted news themes, and NLP-based sentiment- Researched and benchmarked cutting-edge AI tools (LLM, RAG, Deep Research, and etc.)
EDUCATION
American Heritage Schools - Broward Campus
High School Diploma
Columbia University
Master's degree
NYU Center for Data Science
Bachelor's degree
ABOUT HAN GAO
I am passionate about applying advanced ML and quantitative methods to solve complex problems in finance. I am actively looking for data science or machine learning opportunities in the finance industry. If there is any opportunity offered, please reach out to me by Email: c••••••••@gmail.com. Certification:* AWS data engineer Programming Languages -Python (Data Processing, Machine Learning, Automation)-SQL (Snowflake, MySQL, Query Optimization)-Scala (Spark Data Processing) Machine Learning & Data Science - Supervised & Unsupervised Learning (Regression, Classification, Clustering)- Time Series Modeling (ARIMA, SARIMAX, GARCH, CausalImpact, Transformer-based Forecasting)- Deep Learning (Feedforward NN, CNN, RNN, LSTM, GRU, Siamese Networks, Transfer Learning)- Optimization & Regularization (Dropout, BatchNorm, Early Stopping, Hyperparameter Tuning with Ray Tune & Optuna)- Model Evaluation (Cross-validation, ROC-AUC, F1-score, Sharpe ratio, Backtesting Metrics) LLM & RAG - active learning - LLM Application Development (LangChain)- Retrieval-Augmented Generation (RAG)- Fine-Tuning & Optimization (LoRA, Prompt Engineering) Data Engineering & ETL -ETL Pipelines (Fivetran, DBT Cloud, Snowflake)-Data Transformation & Automation (Python, SQL)-Data Quality & Monitoring (Unit & Integration Testing, Logging Systems)-Data Modeling (Real Estate & Retirement Savings Forecasting)-Batch Processing (AWS Batch, Jenkins Job Scheduling) Databases & Big Data -Snowflake, MySQL (Database Management, Query Optimization)-AWS RDS, Aurora (Relational Databases in Cloud)-Spark (Distributed Data Processing)-Cloud Computing & DevOps -AWS (Batch, Lambda, S3, RDS, EC2, EBS, Cloud Integration)-CI/CD Pipelines (Jenkins, GitHub Integration)- Singularity (Environment Setup, Containerization)
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