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General Information

Name Felipe Lorenzi
Email LorenziFelipe7@gmail.com
LinkedIn linkedin.com/in/felipe-lorenzi
Phone (914) 844-9940
Location San Diego, CA

Work Experience

  • 04.2024 – 09.2025
    Graduate Student Researcher
    UC San Diego
    • Conducted research investigating robust and trustworthy data analytics under Dr. Babak Salimi.
    • Co-authored a paper submitted to VLDB 2025 introducing a framework for simulating data quality issues and exposing crucial vulnerabilities often overlooked in even the most robust ML pipelines.
    • Led two research projects on conformal prediction, a robust uncertainty quantification method for AI/ML models.
  • 12.2022 – 10.2023
    Data Analyst
    Hagerty Consulting
    • Built tools and processes from scratch in Python, Excel, and VBA for regulatory compliance in an improvised, emergency response setting.
    • Mediated communications with stakeholders and cross-functional teams belonging to four different organizations.
    • Enhanced data collection processes for improved availability and accuracy while achieving speed ups of over 60%.
    • Conducted QA/QC and developed remediation plans to reduce data discrepancy rates from over 10% to less than 5%.
  • 04.2022 – 07.2022
    Data Scientist Intern
    Neighborly
    • Utilized SQL, statistics, and machine learning models in Python to model franchise success rates in a self-led analysis.
    • Presented analytical findings to C-suite executives and collaborated to conceive actionable insights.
    • Streamlined survey design and data collection pipeline for efficiency and compatibility with future company datasets.
    • Managed project timelines independently while working closely with the business intelligence team.
  • 06.2020 – 10.2020
    Intern
    Catavento Book Distributor
    • Trained and deployed a machine learning model in Python to rectify genre misclassifications of more than 30,000 books by leveraging natural language processing transformer models.

Projects

  • 2025
    Data Management
    • Data Management: Collaborated in a team of three to create recommender system trained on tens of millions of data points scraped from Goodreads using Python, Docker, PostgreSQL, Neo4j, and Qdrant. (2025)
  • 2023
    Forecasting
    • Forecasting: Built database of daily car sales from Cars.com by creating web scraper in Python and analyzed for trends, saving money when purchasing a car a few months later. (2023)
  • 2022
    Machine Learning
    • Machine Learning: Analyzed brain EEG signals when listening to music using signal processing and machine learning in Python using libraries such as mne, scipy, librosa, and pytorch. (2022)
  • 2021
    Statistical Inference
    • Statistical Inference: Analyzed dataset of NYPD civilian complaints using Python to uncover evidence suggesting systematic bias against certain minority groups. (2021)

Education

  • 4.2026
    MS, Data Science
    University of California, San Diego
    • Graduate research in robust and trustworthy data analytics (uncertainty quantification for AI).
  • 8.2022
    BS, Cognitive Science with Specialization in Machine Learning
    University of California, San Diego
    • Data Science minor. 3.7 GPA