Experience
Professional experience across digital experimentation, product analytics, operations, and research.
My current role at Ulta Beauty comes first. The earlier roles show the foundation behind it: stakeholder partnership, KPI definition, dashboarding, quantitative analysis, and clear business recommendations.
At Ulta Beauty, I support A/B and multivariate testing across web and app experiences. The work focuses on defining hypotheses, measurement strategies, KPIs, and success criteria before evaluating how digital changes affect customers and business performance.
What I did
- Support digital experiments by helping define hypotheses, measurement strategies, KPIs, and success criteria.
- Analyze experiment performance with Adobe Analytics, Adobe Target, and Excel across conversion, revenue, engagement, and customer behavior.
- Evaluate statistical significance, sample size requirements, minimum detectable effects, traffic allocation, and test duration.
- Partner with Product, eCommerce, and cross-functional stakeholders to turn business questions into measurable experiments and actionable readouts.
What this demonstrates: practical experience connecting experimentation design, product metrics, statistical reasoning, and stakeholder recommendations.
I contribute to research on how large language models can support interview-based qualitative research without replacing human interpretation. The work combines prompt design, transcript generation, NLP evaluation, qualitative research methods, and practical awareness of tools like Claude, Custom GPTs, MCP-style connections, and n8n automation.
What I did
- Built a GPT-based simulation pipeline that generated AI interview transcripts for 28 founder personas using consistent structured prompts, with patterns transferable to Claude and Custom GPT workflows.
- Compared AI-generated and human interview responses across tone, depth, factual accuracy, strengths, weaknesses, and alignment gaps.
- Developed a Python NLP workflow for thematic coding and sentiment scoring so transcript analysis could be evaluated more systematically.
- Helped design a qualitative evaluation framework with faculty mentors that balances quantitative signals with human interpretation.
What this demonstrates: structured AI-assisted research, qualitative analysis, evaluation, and responsible human oversight.
Through NIU's Experiential Learning Center, I worked on a consulting engagement for a Chicago-based recording studio. The project required turning ambiguous growth goals, fragmented market information, and competitor activity into a structured recommendation set for leadership.
What I did
- Led business analysis across SEO performance, engagement metrics, campaign KPIs, competitor positioning, and customer segments.
- Analyzed 15+ competitor studios to define audience segments, market opportunities, and measurable success criteria.
- Translated fragmented market and demand data into KPI frameworks and strategic recommendations around growth, audience targeting, and marketing investment.
- Owned deliverables from data gathering through executive presentation, incorporating feedback so the final recommendations were practical for a real client.
What this demonstrates: discovery, market analysis, structured recommendations, and presentation to non-technical leadership.
At Shipt, I worked on network planning analytics for a large delivery operation. The role gave me hands-on experience building analytics systems for operational teams that needed better visibility into ZIP-code coverage, daily order volume, and market-level performance.
What I did
- Designed and deployed a Tableau geospatial analytics platform analyzing daily order volume across 30,000+ ZIP codes.
- Helped Market Operations surface delivery blind spots, misconfigured ZIP-code coverage, and high-risk network regions with 30% better KPI visibility.
- Built SQL and Python ETL pipelines to process daily delivery data and automate Tableau extract refreshes, eliminating 10+ hours of manual reporting per week.
- Partnered with Market Operations and Network Planning stakeholders to translate ambiguous operational questions into dashboard requirements and reliable reporting outputs for 5+ planning teams.
What this demonstrates: dashboard development, automated reporting, KPI definition, and decision support for operations teams.
At Innovation DuPage, I supported reporting and operational analysis across program areas. The work focused on making program performance easier to measure, improving Salesforce reporting visibility, and giving leadership more consistent KPI definitions.
What I did
- Built and maintained Tableau dashboards tracking 20+ KPIs across program areas.
- Standardized metric definitions and reporting logic, reducing reporting cycle time by 40%.
- Used SQL and Excel transformation workflows to clean and structure raw program data for downstream analysis.
- Applied Excel-based modeling to identify engagement, utilization, and cohort trends that informed outreach strategy and resource allocation.
- Improved Salesforce CRM reporting workflows so stakeholders had better visibility into program performance.
What this demonstrates: KPI reporting, participant analysis, Salesforce visibility, and decision support in a startup-incubator environment.
My leadership and presentation experience shows that I can communicate technical work clearly, organize professional development opportunities, and present analytics recommendations to people outside the classroom.
What I did
- Won 1st Place in the NIU Data Visualization Competition with HAVI by building a Power BI dashboard using Python and Excel to analyze QSR supply chain inefficiencies.
- Presented findings and recommendations to an industry panel of supply chain professionals and data scientists.
- Founded and chaired OMIS IGNITE, a student-led initiative connecting Operations and Information Management students with professional development, speaker panels, workshops, and networking opportunities.
- Helped coordinate ACM NIU events, promote technical learning opportunities, and connect peers with professional resources.
What this demonstrates: leadership, presentation, organization, and the ability to explain analytics work to real audiences.