Aesthetic Product Data Analyst Resume

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PROFESSIONAL SUMMARY

Detail-oriented and results-driven Product Data Analyst with over 5 years of experience in data analysis, product performance tracking, and reporting. Skilled in SQL, Python, and data visualization tools (e.g., Tableau, Power BI) with a proven track record of delivering actionable insights that drive product improvements and business growth. Adept at collaborating with cross-functional teams to translate data into strategic recommendations and product enhancements.

PROFESSIONAL EXPERIENCE

Product Data Analyst
Tech Innovations Inc. — New York, NY
January 2050 – Present

Analyzed KPIs such as user engagement and churn to drive product strategy.
Developed real-time dashboards and reports using Tableau and SQL.
Conducted A/B tests to evaluate new features, improving user retention by 15%.
Collaborated with product and marketing teams to track and refine product metrics.

Junior Data Analyst
Innovative Solutions LLC — San Francisco, CA
March 2052 – December 2054

Supported product analysis and report generation using Power BI and SQL.
Conducted user segmentation and assisted in optimizing product features.
Improved data quality and reporting accuracy by 30%.

EDUCATION

Bachelor of Science in Data Science
University of California, Berkeley — Berkeley, CA
Graduated May 2050

TECHNICAL SKILLS

Programming Languages: SQL, Python, R
Data Visualization Tools: Tableau, Power BI, Google Data Studio
Databases: MySQL, PostgreSQL, Google BigQuery
Other Tools: Excel, Google Analytics, Jupyter Notebook

CERTIFICATIONS

Google Data Analytics Professional Certificate — November 2051
Tableau Desktop Specialist — January 2052

PROJECTS

A/B Testing for New Feature Implementation

Led the design and analysis of A/B tests to assess the impact of a new search filter feature. Results showed a 25% increase in user engagement, influencing the decision to roll out the feature across the platform.

Customer Segmentation Analysis

Used K-means clustering in Python to identify five distinct customer segments based on behavior patterns. This analysis informed personalized marketing strategies, resulting in a 30% increase in conversion rates for targeted campaigns.