Jen Arriaza
Sr. Data Scientist | Machine Learning Engineer
NY Metro
I build predictive models and automation tools for complex engineering systems.
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Featured Projects
Forecasting Demand & Cost Fluctuations in Supply Chains
Time series modeling with Prophet to forecast chaotic supply chains.
Predicting Failures in High-Risk Production: Aircraft Engines
Evaluating deep learning models to predict failures in high risk production environments.
Classification of Crash Severities & Pre/Post COVID Analytics
Random forest classifier model predicts crash severities in NYC and full report of insights from analytics deep-dive.
Data Science Internship at BMW’s Autonomous Driver Team
Large-scale data analysis and applied machine learning to improve testing and implementation of autonomous driving features.
Publications
Published: Investigating End-user Acceptance of Last-mile Delivery by Autonomous Vehicles in the United States
Co-author. Contributed as student data scientist in completion of academics at NYU. Accepted for publication in May 2022 to Human-Computer Interaction International 2022, and printed to Springer Digital Library.
Published: Sulforaphane Effects on Cognition and Symptoms in Schizophrenia: A Randomized Double-Blind Trial
Co-author. Contributed statistical data analysis on published biomedical research study surrounding the effects of a novel low-toxicity drug. Accepted for publication March 2022 in Oxford Academic.
Senior Research Project: A Study of Autonomous Vehicles: Background, Current Issues, & Outlook of Self-Driving Cars
In-depth research study examining AVs within the automotive/mobility industry.
Past Projects
Analytics Engineering
Trend Analysis in Python using Plotly visualizations. Analyzing historical waste/recycling trends.
Statistical Data Analysis
Linear Mixed Models in SAS Studio. Modeling outcomes of wide-format data and repeated measurements.
Academic Projects
Supervised machine learning in Python to find the cleanest eateries in NYC using health inspection data.