Resume

Tyler Lowry

Data Science Graduate Student

tjlowry02@gmail.com | 480-297-6545 | LinkedIn

Education

Texas A&M University | College Station, TX

Aug 2025 – Present
Master of Science, Data Science (Statistics Track)

Brigham Young University-Idaho | Rexburg, ID

Apr 2025
Bachelor of Science, Data Science – Accounting Minor – Machine Learning Certificate
- GPA: 3.89

Technical Skills

Languages: Python, R, SQL, TypeScript, PHP, HTML, CSS, C# Frameworks/Libraries: TensorFlow, Pandas, Polars, NumPy, Scikit-learn, PySpark, Tidyverse, REST API, React, Node.js
Tools: Docker, Git, AWS, Databricks, Power BI, Tableau, Jupyter, Adobe Suite

Work Experience

Team Lead/Developer

BYU-Idaho McKay Maclab | Rexburg, ID | Jan 2023 – July 2025

  • Designed interactive Streamlit dashboards to track KPI performance, resulting in a 14% average improvement across all metrics
  • Collaborated with a team of 3 in full stack development of Maclab website and 3D printing queue
  • Facilitated weekly meetings to discuss goals, track task progress, and deliver short training sessions to the team
  • Conducted interviews, reviewed resumes to screen candidates, and provided training to new employees

TA/Tutor

BYU-Idaho Department of Mathematics | Rexburg, ID | April 2024 – April 2025

  • Served as teaching assistant and tutor for 5 core courses including “Intro to Programming,” “Data Science Programming,” and “Biostatistics,” plus staffed the Data Science Tutoring Drop-In Lab supporting 200+ students per semester
  • Led weekly group meetings of 10 students and conducted 7-10 individual tutoring appointments per week, focusing on Python, R, Excel, and statistical analysis
  • Graded 100+ student assignments weekly and provided detailed feedback on areas of improvement, while offering real-time problem-solving support for walk-in students across all data science courses

Machine Learning Engineer Intern

PIC Business Systems | San Antonio, TX | May 2024 – Sept 2024

  • Built an ensembled ARIMA + LightGBM model for 90-day item-location demand forecasting, improving median MAPE by 30% over the existing baseline
  • Engineered lag features, rolling statistics, and normalized targets across hierarchical time series to capture seasonality and cross-warehouse demand patterns
  • Integrated external signals (weather, calendar/holiday effects) via API pipelines in Pandas to improve forecast robustness on volatile SKUs

Data Engineering Intern

George W. Lowry Inc. | Salida, CA | Sept 2023 – Dec 2023

  • Reverse-engineered an undocumented legacy database nearing end-of-support by reconstructing the schema from printed documentation and tracing production reports back to source tables, establishing a working knowledge base of the system
  • Led migration from Informix to AWS to support the company’s transition to PetroleumRx for CRM operations, re-architecting the schema by eliminating redundant joins, correcting foreign key relationships, and optimizing indexes — reducing report generation runtime by nearly 2 hours
  • Researched and recommended AWS EC2 instance options tailored to workload requirements, informing a deployment that increased compute capacity while lowering costs and eliminating recurring server crashes that had disrupted daily operations

Research

3D Spatial Transcriptomics Colocalization Analysis

Graduate Research with Dr. Xiaoqing (Jade) Wang, Texas A&M University | 2025 – Present

  • Extending the isoST 3D reconstruction pipeline to intercellular colocalization analysis on the Zhuang-ABCA-2 MERFISH mouse brain dataset (43.1M cells, 1,122 genes), with target submission to Bioinformatics
  • Discovered novel cell-type colocalization patterns detectable only in 3D reconstruction, currently validating against 2D MERFISH baselines and published neuroscience literature
  • Engineered GPU-accelerated pipeline scaling to 43M cells via FAISS k-NN label propagation, lazy PCA loading (192 GB → 9 GB), and adaptive z-thinning for density correction
  • Tech Stack: Python, PyTorch, PyTorch Geometric, FAISS GPU, Scanpy, Google Colab (A100)

Projects

Time Series Forecasting Comparison Dashboard

Senior Capstone Project, 2025

  • Developed comprehensive end-to-end dashboard using Streamlit allowing users to compare multiple forecasting methodologies including ARIMA, neural networks, and ensemble methods
  • Implemented data preprocessing pipeline with Box-Cox transformations, autocorrelation analysis, and seasonal decomposition to reveal trend and seasonality patterns
  • Created educational resources and technical blog to make advanced forecasting accessible to non-technical users
  • Tech Stack: Python, Streamlit, Polars, TensorFlow/Keras, scikit-learn, NumPy

Sales Analytics ETL Pipeline & Dashboard

Statistics and Data Science Consulting Course, 2024

  • Served as data science consultant for a real business client, building a Python/FastAPI ETL pipeline feeding a Tableau dashboard for sales performance across product categories
  • Partnered with stakeholders to translate business requirements into data models and visualizations supporting category-level decision-making
  • Tech Stack: Python, FastAPI, Tableau, SQL

References available upon request