Lesley (Jingyi) Wu

ad0ple@r.postjobfree.com +1-413-***-**** LinkedIn

Education

New York University New York, NY, US

Master of Science in Data Science, May 2025

Language: Python, SQL, R, C++, MATLAB, Java, SAS

Data Analysis and Machine Learning: Tableau, Microsoft suites, SciPy, Matplotlib, Numpy, Pandas, Scikit-Learn, TensorFlow, PyTorch Publications: 1) Risk-aware stochastic control of a sailboat (under review by American Control Conference 2024) 2) Analyses of Tapatan and Picaria (Presented at Nebraska Conference for Undergraduate Women in Mathematics 2022) Mount Holyoke College South Hadley, MA, US

Bachelor of Arts, May 2023 GPA: 3.82/4.00

Major: Mathematics and Philosophy, Data Science Nexus Certificate Relevant courses: Data Science Capstone, Applied Regression, Linear Algebra, Optimization, Statistical Consulting, Data Structure Relevant Experience

Machine Learning Engineer Intern UnionBigData, China Jun 2023 - Aug 2023

● Built a multimodal deep learning model (Resnet and Autoencoder) to predict oil-pumping indicator diagrams, combined with Gibbs model, and optimized architecture by adding fraud detection on indicator diagrams with CNN model (AlexNet) to achieve an overall accuracy of 87%, saving over 30% pumping operation energy

● Implemented an LSTM-based Ensemble deep learning model on time-series well exploitation data to forecast oil wells’ lost circulation, optimizing the operation by achieving 94% prediction accuracy

● Delivered ad hoc support to cross-function teams by proposing potential machine-learning business solutions to stakeholders

● Coded demo for evaluation metrics (AUC, Accuracy, Precision, F-1 score) for multiclass classification on Flink in Java Student Researcher Cornell University, US Jun 2022 - Aug 2023

● Developed a Stochastic Optimal Control model with a risk-averse objective to maximize competitive sailors’ probability of reaching the target in time and implemented the trajectory planning by dynamic programming, with a paper under review by ACC 2024

● Designed and implemented a new algorithm for a mixed-type Stochastic Optimal Control model for customized cancer treatment Student Consultant Statistical Consulting Service at Umass Amherst Sep 2022 - Dec 2022

● Consulted 8 client projects, including experiment design, data cleaning, model construction, statistical analysis, and visualization

● Lead Project: Architected logistic regression model with a large complex stock data set to predict companies’ survival status to obtain model inference validating client’s proposed analysis of company-industry evolution trends Data Analyst Intern Trase, UK Aug 2021 - Apr 2022

● Executed end-to-end data analysis and interactive visualization on soft commodities’ supply chain mapping with 5-year Chinese customs and shipping data to quantify deforestation exposure to enable local government’s data-driven policy decision-making

● Perform desktop research and delivered a 15-page market analysis on promoting sustainable palm oil in the instant noodle industry

● Outreached stakeholders and presented Trase’s supply chain mapping products to promote collaboration on governmental policy-making Intern People’s Insurance Company of China, China Jun - Jul 2019

● Contributed to safety liability insurance bidding with policy desk research, data collection, and visualization of local market analysis

● Delivered a 30-page liability insurance marketing brochure that was distributed to over 20 branch offices

● Managed the 2019 Environment Protection Industry Innovation and Development Conference with over 300 attendees Research and Course Project

Kaggle Project, Identify Age-related Conditions Project Jun 2023 - Aug 2023

● Steered exploratory data analysis, data manipulation, feature engineering, XGBoost model construction, and hyperparameter tuning to achieve log loss of the prediction accuracy on three age-related diseases classification to 1.3 based on biological data Course project from Data Science Capstone, Precision Heart Disease Prediction Project Jan 2023 - May 2023

● Revised published comparative study on machine learning models’ (Logit regression, Support Vector Machine, Decision Tree, Random Forest, Naive Bayes) prediction for heart disease and quantified models’ performance certainty by bootstrapping, with report delivered Student Researcher Polymath Jr., REU program, US Jul 2021- Jan 2022

● Scripted and conducted numerical analysis on the optimal strategy for Abstract Strategy Games to compute winning percentages, with results presented at the Nebraska Conference for Undergraduate Women in Mathematics in January 2022 Student Researcher AIM UP REU program, US Jul - Oct 2020

● Formulated 3 parking function theorems with a simulation model for growth pattern tracking and algebraic analysis

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