Data Analyst Intern

Yushi (Rainie) Dai ******@********.*** 646-***-**** New York, NY

Education

Columbia University, Fu Foundation School of Engineering and Applied Science New York, NY Master of Science in Operations Research, Analytics Track, GPA: 3.58/4.00 Sep 2022 – Dec 2023 New York University New York, NY

Bachelor of Arts in Mathematics and Psychology, GPA: 3.71/4.00 Aug 2018 – May 2022 Key Skillset:

Technical Skills: Python (PyTorch, Scikit-learn, Matplotlib), SQL, Excel (VLOOKUP, Pivot), MATLAB, Tableau, Power BI, R BI Skills: Risk Analytics, Data Visualization, Data Mining, Machine Learning, NLP, Time Series Analysis, Predictive Analytics, Project Management, Process Optimization, Market Analysis, Statistics Analysis, Customer Analytics, Stakeholder Management Professional Experience

Orcasound Data Analyst Seattle, WA February 2024 – Present

• Developed an App for reducing ship noise in preserving whale’s habitat by organizing experts interview and creating affinity maps, a visual to organize information from a brainstorming session

• Sanitized data in Python and created databases by SQLAlchemy and SQLite to store data including trip distances and temperatures

• Visualized a heatmap by transferring coordinate data using GeoPandas and KeplerGL to generate a geospatial visualization of whales’ migration STEALTH Business Insight and Analytics Analyst Intern Irvine, CA May 2023 – July 2023

• Developed an analytics and optimization platform for business monitoring and operation optimization by mining massive amounts of data and extracting useful business insights, delivered a monthly monitoring framework for engineer teams

• Implemented a Salesforce-based platform for continuous monitoring and business experiment, successfully deployed the platform to data science and product management team

• Utilized Python and SQL to develop an analytics suite for data resources, gather requirements, organize sources, and support product launches; saved the overall business operations hours by ~20 hours

• Partnered with external vendor and analytics providers including Veeva and Tableau to research on the existing business streamline and successfully resolved 5 business-related issues and improved the user journey

• Served as an ad-hoc data analyst to research on business deficiencies and successfully delivered 5 findings to the management team Xiaohongshu (RED) Data Operation Analyst Intern Shanghai, China May 2021 – August 2021

• Implemented a BI framework for generating insights and analytics, and developed a business tracking tool for continuous improvement purposes to improve ads relevance and quality for end users

• Partnered with stakeholders from data science division and business analyst division to develop a metrices development suite including products metrices/monitoring metrices/analytics metrices; saved the overall R&D costs by 10%

• Developed a business governance tool for formulation and product monitoring purposes, and increased the overall product delivery by~15%

• Collaborated with the marketing team to design and conduct focus groups, utilized SQL queries collecting feedbacks to identify targeted users BeyondSoft Operation Analyst Intern Guangzhou, China June 2020 – August 2020

• Posted 8 targeted positions and reviewed suitable candidates, screened 3,000 resumes and 1,000+ potential job seekers for initial phone screens

• Assisted the team to assess KPI to review new employees’ performance, reported new employees into the system by setting up payrolls

• Designed compensation and incentive plans in accordance with the requirements of the company's guidance documents, and assisted the company's HR team to optimize and improve the compensation and performance system Postal Savings Bank of China Data Analyst Intern Guangzhou, China December 2019 – February 2020

• Developed Machine Learning-based financial analytics and performance measurement model for business research and reporting

• Initiated data-driven evaluations of credit cards and financial products, and delivered market research and business discovery reports that aligned offerings with segmented customer demographics, influencing marketing strategies

• Orchestrated data ETL and visualization utilizing Excel and Python, analyzed product performance across markets and presented key insights

• Collaborated with the FP&A team to monitor and reduce campaign costs, achieving a 15% reduction in overall expenses Project Experience

Prediction and Recommendation System of Spotify Tracks (Python) Columbia University May 2023

• Engineered and fine-tuned 4 predictive models, including XGBoost and Logistic Regression, using a Kaggle dataset. Achieved a high precision score of 0.973 in Random Forest, demonstrating robust predictive capabilities

• Built a recommendation engine using cosine similarity metrics, significantly enhancing user engagement by 35% and increasing average session duration by 15%. Collaborated with a cross-functional team to validate the model's effectiveness

• Implemented Spotify API by Python to visualize the recommended playlists with album covers based on the selected tracks Risk, Uncertainty, and Resiliency in an Airport Project (Python) Endorsed by consulting firm Autocase September 2022 – December 2022

• Led a team of 4 in creating a Python algorithm to prioritize funding across multiple capital investment projects, identifying the most cost- effective alternatives and assessing the impact of input uncertainties

• Conducted data analysis on 23 assets by performing correlation and sensitivity analysis to identify key variables affecting savings and payback

• Developed an interactive decision support system featuring intuitive algorithms and visualizations, enabling the client to efficiently make data-driven decisions in airport location optimization

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