Lead end to end data processing including data collection, processing, analysis, and visualization. - Developed and implemented new data systems, transforming Great MN Schools’ data practices from unhygienic, disparate, inconsistent data reporting to a streamlined, accessible, and consistent infrastructure that allowed Great MN Schools team members to easily access data and create shared ownership - Instituted innovative data analysis methods, including a Similar Schools Model that allows Great MN Schools to more faithfully compare portfolio schools to those that serve similar studentsSpearhead, design, and execute product and project management for Minneapolis School Finder, a family-facing tool containing information on 147 Minneapolis-serving schools implemented via a website with attracted over 16,000 site visits and a book with over 2,000 copies distributed in FY2024 - Oversee multiple incongruous vendors to ensure faithful execution of deliverables on the 6-month project timeline and within a $145,000 budgetAdvocate for local and state level data quality, data transparency, and school accountability - Design and lead data calculations and visualizations for Minneapolis School Finder Rating, an innovative and holistic metric that describes school quality in a way that is accessible for students, parents, and families - Facilitate a working group of policy, school, and community experts to design and implement an innovative academic rating system for alternative high schools in Minneapolis-Supervise a $35,000 grant to research, engage, and advocate for an improved Minnesota Student Survey as well as a more statistically sound MCA Growth metric

In my role in the marketing sciences and audience solutions teams, I touched all facets of Kinesso's client-facing work from new business pitches to modeling and priority insight presentation. I drove analytically founded media marketing solutions by building marketing mix models, full funnel models, and optimized media scenarios. These resulted in boosts to brand awareness, market share, and sales outcomes. In the post-modeling phase, I built and maintained presentations and dashboards that enabled clients to interact with and understand granular data and model insights. Throughout each stage of my work, I collected, validated, and analyzed data across sources and clients, creating automation routines where possible. I also combined CRM data with powerful propensity and demographic information to model, build, and activate high value audiences. Industries touched include but are not limited to mortgage lending, automotive, CPG, pharmaceutical, and financial services.

I collaborated in a team of 5 in client-focused, human-centered design thinking. We developed methods to improve buy-in from Princetonians in the upcoming Princeton climate action plan by building relationships with and interviewing dozens of community leaders, local business owners, and residents. We then analyzed data by applying behavioral science concepts, forming affinity maps, and dichotomizing interviewees to connect faraway dots, draw novel insights, and locate design opportunities. Those insights and design opportunities inspired over 400 ideas, 11 of which were developed. The final product prototyped a gamified engagement platform for Princeton youth which we found would allow outreach to parents and the community at large.

In one project, I identified and evaluated issues in stormwater pipes that impacted flooding in the lower levels of the city. I also worked to improve the efficiency of maintenance to identify problem areas before they arise.

I prepared and gave lessons to two small classes of 7th grade students -- largely from socially disadvantaged backgrounds -- on pre-algebraic concepts. The work in and out of the classroom catered toward placing students in a collegiately oriented mindset, emphasizing the importance of education in all daily operations. The program also gave me experience operating around budget constraints and arranging logistics for large-scale events.