Aspiring Data Analyst - Python, ML, Visualization

STEVEN SUO

DATA ANALYST INTERN 669-***-**** San Jose, California Email LinkedIn

Summary

Aspiring Data Analyst with hands-on experience in statistical modeling, data visualization, and predictive analytics using Python, R, and SQL. Strong analytical mindset with academic project experience in machine learning and data science. Seeking internship or entry-level opportunities to apply data skills and grow within the tech and analytics field.

Skills

●Programming & Analysis: Python (Pandas, NumPy, Scikit-learn), R, SQL

●Data Visualization: Tableau, Power BI, Matplotlib, Seaborn

●Machine Learning: Regression, Feature Selection, Correlation Analysis, NLP (TextBlob)

●Excel (Advanced): Pivot Tables, Conditional Formatting, Advanced Charting, Solver, Data Tables, VBA & Macros

●Tools: GitHub, Power BI, Excel

●Soft Skills: Creative problem solving, teamwork, adaptability, communication, attention to detail

Education

University of British Columbia (UBC) Bachelor of Science in Mathematics BC, Canada 2023 – Present

Work Experience

Banking & Quantitative Solution

Data Analyst Intern Pasadena, CA 09/2022- 10/2022

●Developed and tested a machine learning model to identify relevant features and predict key drivers of financial data.

●Applied Python (Pandas, NumPy, Scikit-learn) to clean datasets, run correlation analysis, and perform linear regression for predictive modeling.

●Created data visualizations to compare actual vs. predicted values and presented insights in weekly team meetings.

●Contributed to improved forecasting accuracy and demonstrated ability to work with real-world business datasets.

Project Experience

Amazon Consumer Review Sentiment Analysis (Python, Power BI)

●Analyzed 20,000+ Amazon customer reviews to extract keywords and sentiment scores, identifying key factors affecting ratings.

●Applied TextBlob (Python) for natural language processing and built interactive Power BI dashboards to visualize sentiment distribution, review length patterns, and rating trends.

●Generated insights showing shorter reviews often contained extreme sentiments, while longer reviews provided more objective feedback.

●Proposed business optimization strategies, such as improving product images and enhancing customer service communication, to boost e-commerce conversion rates.

Electric Vehicle Data Processing & Visualization (Python)

●Processed and cleaned EV performance datasets; standardized data types and prepared for analysis.

●Built visualizations (Matplotlib, Seaborn) to identify relationships between cost-efficiency, battery size, and efficiency.

●Discovered that efficiency, rather than battery size, was the most important factor in cost-effectiveness.

Data Scientist Job Salaries Prediction Model (R, Team Project)

●Analyzed dataset of global data scientist salaries to identify key predictive factors.

●Built and validated a regression-based predictive model using R.

●Summarized project requirements and contributed to exploratory data analysis and model evaluation.

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