Data Science Engineer with Finance Focus

Evan Perez

************@*****.*** 479-***-**** Github/evanperez444 https://www.linkedin.com/in/perezevan/ EDUCATION

The City College of New York – Grove School of Engineering New York, NY M.S. in Data Science and Engineering, Concentration in Finance, GPA: 3.33 Expected May 2027 B.S. in Computer Science, Minor in Mathematics, GPA: 3.47, Cum Laude Awarded May 2025

§ Coursework: Algorithms, Data Structures, Linear Algebra, Probability Theory, Mathematical Statistics

§ Honors: Princeton P3 ORFE Scholar, EY Mentorship Fellow, Futures in Finance Fellow, Tau Beta Pi HS SKILLS

§ Programming: Python, R, SQL, C++, Azure, Visual Studio Code, MySQL, Git/GitLab, Microsoft Excel

§ Libraries: Pandas, SciPy, Giotta-TDA, WhaleWisdom, Scikit-Learn, Matplotlib, TensorFlow, PyTorch WORK EXPERIENCE

Royalty Pharma (Biotech Investment Firm) New York, NY Search & Evaluation Data Science Intern June 2025 – August 2025

§ Identified 3 high conviction stocks across 30+ funds by building a Python tool to extract data from an SEC Filings API

§ Feature engineered a dataset of 1000+ positions to calculate the total market value and concentration of biotech portfolios

§ Performed a multi-time series analysis of quarterly changes in share volume for a specific stock using Microsoft Excel Air Force Research Laboratory New York, NY

Machine Learning Research Assistant December 2024 – Present

§ Achieved 80% accuracy in classifying 3D point clouds by experimenting with LightGBM, XGBoost, and Random Forest

§ Identified anomalies by building an ML system to identify damaged aircraft parts using Part Segmentation and Isolation Forest

§ Preprocessed a dataset of 12,000+ samples by applying topological data analysis to reduce dimensions into feature vectors

§ Leading one intern in an experiment to compare performance in mathematical analysis for topological data analysis methods Harvard & Smithsonian Center for Astrophysics Cambridge, MA Signal Processing Research Assistant (NSF REU) June 2024 – Present

§ Conducted a time-frequency analysis of 150+ X-ray emission samples using Fourier and Wavelet Transforms

§ Reduced spurious patterns by applying convolutional kernel smoothing and isolated oscillatory patterns by detrending

§ Discovered significant periods between 20 – 40 sec by visualizing light curves on top of scalograms using Matplotlib IQSpatial New York, NY

Machine Learning Engineer Intern June 2023 – June 2024

§ Developed RAG prototypes for a Fortune 500 client to extract text data from 500+ PDFs using LangChain and NLTK

§ Achieved 84% accuracy in detecting blue tarps in satellite imagery and extracting geospatial coordinates using YOLO Ursa Space Systems Ithaca, NY

Data Science Intern June 2022 – August 2022

§ Reduced data preprocessing time by 70% by building a Python CLI tool to transform 1000+ CSV files into GEOJSON

§ Retrained an object detection computer vision model to detect naval ships on newly processed data using AWS-EC2 CONFERENCE PRESENTATIONS

§ [1] Perez, E. A. (2025, September). Efficient and High-Performance Analysis for Sparse 3D Point Cloud Data via Deep Learning Multimodal Data Fusion and Mathematical Analysis. Air Force Research Laboratory Demo Day, Rome, NY

§ [2] Perez, E. A. (2024, December). Data Exploration in Search of Small Pulsations in Solar X Ray Flares with Hinode/X Ray Telescope (XRT). American Geophysical Union Meeting, Washington, D.C. Abstract ID 1711621 PROJECT EXPERIENCE

Time Series Energy Price Prediction with Long Short-Term Memory (LSTM)

§ Forecasted electrical prices with 96% accuracy by building a recurrent neural network and a dataset of 1000+ samples

§ Performed data exploration using Pandas and combined energy and weather data for multivariate time series forecasting

Contact this candidate