Samantha Schmid | Operations Analyst

I make complex systems clearer, smarter, and easier to use.

I’m an Operations Analyst with an engineering background and a bias toward making complex work simpler. I work across data, process, and product, using analysis, automation, and technical problem solving to improve how systems run. Outside my role, I build consumer apps and analytics projects that turn ideas into useful, working products.

Degrees

• M.S. in Business Analytics | 2026–2027
• B.S.E. in Mechanical Engineering | 2022–2025

Recent Roles

• OpenAP | Operations Analyst
• General Dynamics Mission Systems | Manufacturing Engineer Intern
• Nissan Motor Co. | Powertrain Test Intern

See Projects Download Resume LinkedIn GitHub

Employment

Operations Analyst

OpenAP

09/2026 – PRESENT

• Manage data operations workflows across publishers, agencies, and data partners, including file preparation, transformation, validation, QA, and delivery.
• Use Python, Google Colab, Excel, Snowflake, and cloud based platforms to work with large datasets and support advertising audience activation.
• Improve recurring workflows through automation, documentation, troubleshooting, and process standardization.

Manufacturing Engineer Intern

General Dynamics Mission Systems

09/2025 – 12/2025

• Supported manufacturing engineering activities for the Air and Missile Defense Radar (AMDR) program in a high-reliability defense environment.
• Assisted with process documentation, cross-functional coordination, and production support to improve manufacturing execution.
• Contributed to engineering work tied to complex system build quality, readiness, and workflow efficiency.

Powertrain Test Intern

Nissan Motor Co.

05/2024 – 08/2024

• Executed powertrain test runs and collected measurement data to support engine calibration and performance evaluation.
• Organized, cleaned, and analyzed test data to identify trends, compare calibrations, and support engineering decisions.
• Built clear visuals and summaries to communicate findings and recommend adjustments for more efficient, consistent test workflows.

Intelligence

Arizona State University

Master of Science in Business Analytics

January 2026 – May 2027

GPA: 4.0

Major Map ↗

Arizona State University

Bachelor of Science in Mechanical Engineering

August 2022 – December 2025

GPA: 3.3 / 4.0

Major Map ↗

East Valley Institute of Technology

Automotive Technologies

July 2021 – May 2022

GPA: 4.0 / 4.0

Chandler-Gilbert Community College

Dual Enrollment

July 2018 – May 2022

GPA: 4.0 / 4.0

Casteel High School

High School Diploma

July 2018 – May 2022

GPA: 4.0 / 4.0

Independent Learning

Analytics & Data

• SQL
• Python
• Excel
• Power BI
• MATLAB

Engineering

• SolidWorks
• ANSYS

Product & Development

• React
• Next.js
• Supabase
• Vercel
• Visual Studio Code
• Wix Studio

All Certifications

Favorites

Projects

Exhibit A

AI-assisted wellness app and companion manuscript focused on everyday environmental exposure reduction.

●Uses guided quizzes, prioritization logic, and action-based planning.
●Built with AI-assisted product ideation, feature definition, content structuring, and UX refinement.

Download PDF

PREVENTABLE DEATH MAP

County-level analytics dashboard identifying patterns linked with premature mortality.

●Built with Python, CDC WONDER, CDC PLACES, ACS, scikit-learn, GitHub, and Power BI.
●Analyzes county risk factors, high-risk regions, socioeconomic patterns, and model results.

VIEW DASHBOARD VIEW GITHUB

Been There. Done That.

Interactive travel app for tracking where you’ve been and turning travel history into a visual record.

●Map based tracking for countries, cities, places, and trip history.
●Designed and built as a consumer product with a visual, map first experience.

VIEW ON APP STORE

RoutineOS Habit System

Habit system app prototype for structured daily planning and repeatable routines.

●Built around layered routines, sub-habits, and progress logic.
●Turns messy planning into repeatable day to day execution.

Launch RoutineOS

Radar-Readable Sign for Autonomous Vehicles

Engineering capstone focused on radar-readable sign geometry for autonomous vehicles.

●Designed to improve signal return consistency in poor weather and low-visibility conditions.
●Combines engineering design, testing, and performance evaluation.

View Capstone Report