Sam Russel

Volunteered to redesign and rebuild the public-facing WordPress website for Detroit’s LGBTQ+ youth services nonprofit. Focused on improving accessibility, content organization, and overall digital presence.

Co-led the design and build of an AI-powered natural language querying tool on Ally's Snowflake data from the ground up, owning technical direction. Iterated on prompt design and query logic to generate accurate, reliable SQL for real business questions, and supported adoption through training and office hours.

Provided weekly one-on-one English language tutoring for adult learners. Built tailored lesson plans and adapted communication style to support students’ goals.

Co-leads Ally’s Detroit Pride employee resource group, hosting internal events and external speakers/workshops. Manages group discretionary spending and donations and helps maintain visibility through Motor City Pride.

Provided weekly mentorship to residents by offering consistent emotional support and serving as an advocate and role model. Transitioning to the Ambassador Program to learn community needs, build connections, and raise awareness for Vista Maria’s mission.

Owned data quality vetting for an enterprise customer data consolidation initiative, building validation frameworks from scratch for multiple business lines. Translated fragile Excel-based workflows into Sigma dashboards, and conducted exploratory/statistical analyses on Snowflake datasets to deliver executive-ready reports and self-serve dashboards.

Defined and tracked monthly KPIs for digital product performance, building dashboards to communicate insights for non-technical stakeholders. Mapped cross-team information flows to clarify data ownership and reduce duplication.

Analyzed athlete data with Python in Jupyter to address descriptive and predictive questions related to health, safety, and performance. Condensed findings into visualizations using Tableau for a diverse, non-technical audience.

Cleaned and catalogued large-scale survey data in OpenRefine and modeled variable relationships in R as part of a dataset built from nearly 15,000 household surveys. Synthesized patterns across household interviews using statistical concepts and presented findings to mixed technical and non-technical audiences.

Certificate in Applied Generative AI at Johns Hopkins University (remote) for 100 hours (10 CEUs) from 2025–2026.

Grade: GPA: 3.96/4.0

Master of Applied Data Science at the University of Michigan (remote) from 2022–2025 (GPA: 3.96/4.0).

Grade: GPA: 3.95/4.0

Bachelor of Science in Information at the University of Michigan (2017–2021) with a minor in Statistics (GPA: 3.95/4.0).