Jennifer Zhang

About Me
I’m passionate about building products at the intersection of technology, business, and social impact. I enjoy working on interdisciplinary teams to turn complex data and user insights into thoughtful, scalable solutions. My experience spans product research, AI-driven solutions, and go-to-market strategy — all grounded in a strong interest in using innovation to solve real-world problems. I'm especially drawn to mission-driven work that drives access, equity, and long-term value for communities. I approach every project with curiosity, clarity, and a focus on impact.

What are some of your key professional/career interests?
Project Management, Strategy & Operations, Tech4Good

What are some of your skills?
C++, Python, R Studio, SQL, Tableau, Linear Programming, Gurobi Optimizer, Machine Learning, Market Research, Data Visualization, Cross Functional Collaberation

What are some relevant classes/coursework you have taken?
Machine Learning, Data Structures and Algorithms, Discrete Maths, Advanced Management Operations, Advanced Business Finance, Data Analytics & Statistics

What are some of your projects or achievements?

Product Marketing Analyst @ Micron Technology:

- Programmed a Python-based AI automation solution to classify new Amazon SSD and DRAM product drops, reducing a 10-day manual process performed every quarter to under a day, accelerating team-wide efficiencies

- Simulated product sales using Monte Carlo methods on Amazon badge data, modeling daily purchases with Python to estimate 30-day trailing sales and identify high-growth SKUs with ~70% accuracy

Tech4Good Conference Co-Lead:

- Led a 10-person team to execute USC’s inaugural Tech4Good Conference, managing a $7500 budget, and securing participation from 10 leading ethical tech companies - GoGuardian and Snowflake - and 5 C-suite panellists

- Coordinated a month-long marketing campaign that generated over 45,000 impressions, managed speaker outreach, and oversaw key milestones to deliver an event that reached 100% capacity with 250+ engaged attendees

Project:

- Built a discrete simulation in Gurobi of pedestrian flow at USC checkpoint using 3000+ self-collected data points, modelling scanner prioritization, human disruptions, and service-time variability to reflect congestion patterns

- Designed a 4-lane system reconfiguration leveraging existing infrastructure, which reduced average wait times by 93.4%, validated through 100+ simulation replications and robustness testing with confidence intervals