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Contact

Skills

Mathematical Modeling

Machine Learning

Data Analytics and Visualizations

Statistical Analysis

Nanotechnology

Web Design

Programming

Python

R

SQL

Javascript

Matlab

Tools

Tableau

HTML/CSS

Looker

AWS

Adobe

Main

Hannah Luebbering

Data scientist with +2 years in machine learning and data engineering. Built live dashboards for 40+ stakeholders and deployed a dbt-driven ELT pipeline that automated daily data ingests and slashed pipeline costs by over 50%. First author on a 2023 Cell Reports Physical Science published research paper, translating complex data into actionable insights and driving seamless cross-team collaboration.

Education

University of Washington

Master of Science - Data Science

N/A

2021\(\bf\hbox{-}\) 2023

Wake Forest University

Bachelor of Science - Applied Mathematics

N/A

2017\(\bf\hbox{-}\) 2021

  • Association for Women in Mathematics, Executive

Experience

Data Scientist, Digital Advertising Analytics

VuePlanner

New York, NY

May 2023\(\bf\hbox{-}\) Present

  • Mined million-row DV360 datasets in BigQuery/Python to surface new audience & placement levers, boosting strategic YouTube/Google Ads bids and raising ROAS by +5% in one week.
  • Built live Looker Studio dashboards for 40+ stakeholders, eliminating manual ad-hoc reports and accelerating scalable KPI visibility.
  • Developed NLP data pipeline system (spaCy + UMAP + HDBSCAN) that clusters 100k+ YouTube keywords into high-intent themes, sharpening contextual targeting.
  • Deployed dbt-driven ELT framework in BigQuery, fully automating daily ingests and slashing pipeline costs by 50% within two quarters.

Nanotechnology in Solar Cells Research

Elham Ghadiri’s Nano-Photochemistry Lab

Wake Forest University

Oct 2018\(\bf\hbox{-}\) May 2021

  • Acquired photoluminescence imaging, spectroscopy, and ultra-fast pump-probe microscopy data from solar cell devices, wrangling 100 GB+ of hyperspectral data.
  • Built Python/MATLAB pipeline (PCA segmentation, histogram clustering, non-linear lifetime fits) that transformed raw spectra into grain-level maps, cutting runtime by 30%.
  • Analyzed data to identify key photophysical processes and evaluate device performance of nanostructured films; published as first author in Cell Reports Physical Science in 2023.

Data Science Pedagogy Research

Lucy McGowan’s Lab, Wake Forest University

Winston-Salem, NC

Jan 2020\(\bf\hbox{-}\) Mar 2021

  • Engineered Shiny learning platform that auto-assigns students to learn either tidyverse or base-R first, delivering interactive tutorials and auto-graded coding exercises.
  • Orchestrated crossover A/B randomized-controlled trials (n > 100), showing a tidyverse-first sequence measurably boosts statistical-programming proficiency.
  • Captured in-app telemetry (clicks, demographics, assessment scores) and fit mixed-e ects models to reveal factors that improved retention & comprehension over 15 weeks.

Data Visualization & Analytics Intern

Empower Retirement

Greenwood Village, CO

May 2021\(\bf\hbox{-}\) Feb 2022

  • Segmented AWS NetApp, Commvault & AppStream usage logs in Python/SQL to identify business-unit spend outliers, reducing monthly cloud costs within 12 weeks.
  • Developed cross-functional Tableau dashboards monitoring real-time cost, capacity, and utilization data, cutting weekly operations-review time by 30%.
  • Forecasted cloud storage capacity 14 days ahead with Prophet/ARIMA models, giving infrastructure teams time to provision resources and avoid cost spikes.

Extracurricular

Association for Women in Mathematics Executive Committee

Wake Forest University

Winston-Salem, NC

2019\(\bf\hbox{-}\) 2021

  • Co-led monthly math workshops for 30+ students and guided a peer-mentoring tutoring program pairing struggling learners with top performers, scaling one?on?one support department-wide.