about.txt

Nico Ceresa

// Domenico Ceresa

I'm a Computer Vision & ML Engineer based in the Bay Area, specializing in perception pipelines and real-time inference systems. I recently wrapped up three years at BPM LLP building automation tools, data pipelines, and AI-powered solutions. I'm currently pursuing my M.S. in Computer Science at Georgia Tech with a specialization in Artificial Intelligence. For fun, I enjoy rock climbing, photography, hiking, snowboarding, reading, and playing guitar.

currently: Seeking CV & ML Engineer roles · M.S. CS (AI) @ Georgia Tech (4.0 GPA)
interests: Computer Vision, ML Engineering, Perception Systems
location: San Francisco Bay Area, CA

education.txt

Education

Georgia Institute of TechnologyAug 2025 – Jun 2027

M.S. Computer Science — Artificial Intelligence

4.0 GPA

Atlanta, GA

University of OregonOct 2019 – Jun 2023

B.S., Data Science

Minors in Computer Science & Mathematics · Major GPA: 3.88/4.00

Eugene, OR

experience.txt

Experience

Data Analyst · BPM LLP · San Francisco, CA

Jun 2024 – Apr 2026

–Engineered an NLP pipeline integrating Azure Cognitive Services and GPT-4 to extract and summarize key data from 100+ page transfer pricing reports, reducing analyst preparation time by ~98% (4 hours to ~5 minutes)
–Applied fuzzy matching algorithms to reconcile invoice line items against project estimates, generating automated PDF outputs and reducing processing time from ~5 hours to under 1 minute
–Built a simulation model to optimize intercompany renewable energy transfer pricing, maximizing profit through Canadian carbon credit monetization
–Designed Power BI dashboards tracking operational KPIs, giving leadership visibility into firm performance

Data Analyst Intern · BPM LLP · San Francisco, CA

Apr 2023 – Jun 2024

–Developed Power BI dashboards to surface key metrics and employee performance, providing clientele visibility into their data
–Conducted research and synthesized findings to support senior analysts on client engagements, contributing to data-driven recommendations and deliverables
–Collaborated cross-functionally with leadership and business teams to communicate data insights and support strategic decision-making

Data Science Learning Assistant · Univ. of Oregon, Data Science Dept. · Eugene, OR

Dec 2022 – Mar 2023

–Facilitated weekly office hours supporting 50+ students in regression, KNN, gradient descent, decision trees, and bootstrapping