Jesse Anderson

Data analytics professional with proven expertise in transforming complex datasets into actionable business insights. Experienced in advanced analytics techniques and processing large datasets (50,000+ data points) using Python for executive-level reporting. Developed a C-suite reporting framework achieving 93% implementation rate and improved data quality verification processes, increasing coverage from 80% to 98%.

Passionate about leveraging data science to solve meaningful business challenges while maintaining a meticulous attention to detail and commitment to accuracy. I combine strong technical capabilities with effective communication skills, allowing me to translate complex analyses into clear narratives that drive strategic decision-making.

Associate Client Manager, NielsenIQ – Baltimore, MD June 2022 – Present

• Automated data quality verification process using Python, improving item coverage from 80% to 98% and saving over 200 hours of manual work annually
• Standardized monthly C-suite Omnichannel reporting leveraging Panel data and RMS, resulting in 93% of recommendations being implemented in client strategy
• Spearheaded end-to-end category review process for Sally Beauty, from devising initial framework to successfully delivering over 10 categories per year to the merchandising team
• Conducted critical pricing analysis for Amazon's CEO by processing 50,000+ data points within a two-day deadline using Python and RMS, earning NIQ's Innovation Award

• Co-authored two academic papers for the 2022 CHI Conference examining technological adaptation and dementia progression
• Conducted mixed-methods data analysis from user interviews, identifying usability challenges and generating actionable design improvements
• Translated complex research findings into practical interface design recommendations for assistive technologies

• Developed advanced data visualization models using GeoPandas for geospatial analysis of socioeconomic patterns
• Cleaned and incorporated 100K+ data points into recommendation algorithm using Python that identified 10 critical regions for targeted intervention
• Directly influenced educational campaign strategy on the child tax credit through data-driven insights and visualization

• Generated comprehensive reports on policy impacts covering emerging technologies including ML, AI, and quantum computing
• Mapped policies and created detailed blog posts for 200+ organizations at the forefront of computing research
• Analyzed policy implications through quantitative and qualitative data assessment methodologies

Project Owner, ChatHealth 

• Directed end-to-end redesign of student health resources website, increasing student engagement by 43%
• Implemented W3C Accessibility Standards through HTML/CSS modifications and ARIA attributes for 4,000+ users
• Successfully managed fundraising efforts, raising over $10K through campus challenges

• Developed Python-based sentiment analysis pipeline using NLTK and machine learning to analyze 20,000+ tweets
• Engineered data cleaning and preprocessing workflows to handle large-scale social media text data using Twitter API
• Synthesized findings into a research paper published by the American Political Science Association

University of Maryland  – Bachelor’s in Data Science May 2022