Data Analyst Science

Jessie Ren

******.*****@*******.*** · 217-***-**** · LinkedIn · Illinois (Open to Relocation) · Tableau EDUCATION & TECHNICAL SKILLS

University of Illinois Urbana-Champaign, Gies College of Business, Champaign, IL Expected May 2026 M.S. in Business Analytics (STEM designated program) Specialization: Algorithms in Analytics - GPA:3.97 /4.0

● Major Coursework: Statistic, Data Science and Analytics, Data Storytelling, Communication with Data Shenzhen University, Shenzhen, China Sep 2019 - Jun 2023 B.S. Administration in Management - GPA:3.84 /4.0

PROFESSIONAL EXPERIENCE

Data Analyst Extern, Beats by Dre Data Analytics May 2025 – Expected Aug 2025

• Created a Customer journey map by identifying user behaviors, pain points, and emotional touchpoints across stages, with a key hypothesis that the main pain point was related to perceived value for money.

• Cleaned 5k+ quantitative and qualitative data in Excel in preparation for analysis; created visualizations (bar charts, histograms, scatter plots) based on Likert-scale analysis of customer purchase preference and price sensitivity.

• Built an Explanatory regression model via Python to analyze how customers’ perceived importance of product features

(e.g. sound, battery, price, etc.) influences satisfaction, identifying durability and price as the strongest drivers. (P = 0.04)

• Conducted Sentiment analysis using TextBlob to quantify customer satisfaction trends, uncovering that price-related complaints accounted for 65% of negative sentiment. Data Analyst Intern, Eth Tech Dec 2024 – Feb 2025

• Conducted data cleaning on 55K orders across 35+ countries during the past 12-month in SQL and examined missing data for 11 variables to ensure data integrity and handled 10K+ outliers via the IQR method.

• Performed correlation analysis across 8+ key features via Python, identified Early Adopters contributing to 60% total sales and proposed promotional strategy targeting Variety Seekers to bring 20% incremental revenue.

• Designed end-to-end Tableau dashboard to illustrate total spending by location with pie charts, distribution plots, bar graphs, and linear regression plots and supported data-driven decision for sale diversification strategy.

• Conducted A/B test to evaluate price anchoring effects for original price vs. with strikethrough and analyzed statistical significance using t-tests (p < 0.002) to assess impact on early adopters’ brand loyalty and purchase intent.

• Conducted RFM analysis to segment 4K+ customers and applied Elbow Method with K-means clustering to uncover three categories (VIP, Potential, At Risk), visualized segment distribution to identify actionable insights for customer retention strategies.

Data Analyst, Road Ready Wheel, IL Aug 2024 – Dec 2024

• Consolidated past 5-yr inventory, web analytics data from Oracle Database, Hotjar & Google Analytics across 1.2K+ customers, cleaned 15% invalid sessions and imputed missing values with median-based methods.

• Identified key user segment that drove significant MOM revenue decline and analyzed thorough user behavior funnel to uncover 37% cart abandonment rate & 48% checkout completion rate for further optimization.

• Designed an interactive Tableau dashboard to visualize key metrics trendline (browsing time, completed checkouts) and monitor unit price & advertising spend impact on sales growth, providing strategic insights to pivot revenue loss trend.

• Built multivariate linear regression to evaluate the impact of product pricing, advertising spend, and web traffic on sales performance for new customers via Python, successfully identified product pricing as the primary driver for cart abandonment as new customers being 2.3x more price-sensitive. Data Analytics Consultant Intern, McKinsey & Company Jun 2024 - Aug 2024

● Built SQL queries to consolidate historical 10-yr macroeconomic indicators (GDP, CPI, population growth, consumer spending) & industry metrics (market size, user growth, penetration rate) across 35 potential market penetration cities.

● Cleaned 100K+ records with 12% missing values median imputation and identified outliers through IQR filtering.

● Established a Tableau dashboard to illustrate time-series trendlines and geographic heatmaps highlighting high-growth regions and drove 10 executive reporting to support ~$5M strategic growth expansion.

● Developed K-Means clustering with Silhouette Score validation to categorize cities into high, moderate, low-growth tiers and successfully identified top high-growth markets driving 45% total market potential.

● Designed a multivariate linear regression model with Python (StatsModels) and forecasted potential market growth rate based on GDP growth, population & competitive intensity to support market focus prioritization strategies. TECHNICAL SKILLS

● Programming Language: SQL, Python (Pandas, NumPy, StatsModels, Seaborne, Matplotlib)

● Visualization & Tools: Tableau, Power BI, Advanced Excel, Advanced Microsoft Suits

● Statistics & Machine Learning: Multiple Linear Regression, Testing, Factor Analysis, Time Series Forecasting, Classification Models (Logistic Regression), Clustering Analysis (K-Means)

● Hobbies & Languages: Table Tennis (National Level), Golf, Mandarin Chinese (native), English (advanced)

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