Gretchen Riggs
Data Scientist / Machine Learning Practitioner
EXPERIENCE
The Bee Corp, Denver, CO
Data Scientist
Jan 2018 – April 2023
Aided & managed the data science team in the creation of Verifli, a product that grades the health of beehives using infrared hive imagery & machine learning in the AgTech space, going from idea origination to market in less than nine months. Putting into production Queen’s Guard, a product used in evaluating the health of the queen bee, and QGPS, a product used in hive theft prevention. Trained models for Image segmentation. Performed customer discovery analysis, data collection via web scraping & APIs, and created visualizations.
Data Science Consultant - Denver, CO
March 2017 - Jan 2018
Gathered data via web scraping, performed data analysis, made statistical inferences, created visualizations, and interpreted the results in the healthcare, safety, & home improvement industries. ION Geophysical, Houston, TX & Denver, CO
Project Manager/Senior Processing Geophysicist
JULY 2005 - JULY 2016
Performed data analysis, data visualization, anomaly detection, transformation, and signal & image processing on seismic data, managing the project’s status along the way and increasing productivity by 30% through an introduction of more efficient methods. Presented results to clients, communicating in a clear manner the algorithms applied to their data.
EDUCATION
Galvanize Data Science Immersive, Denver, CO
Data Science Fellow
DECEMBER 2016 - MARCH 2017
Fast-paced and hands-on Data Science Immersive Program, grounded in Python.
Missouri University of Science & Technology,
Rolla, MO
B.S. Applied Mathematics
AUGUST 1996 - MAY 1999
CAPSTONE PROJECT
Nature or Not?: Detection of Man-Made Structure from Satellite Imagery — Capstone Project
Training a convolutional neural network to recognize the presence of man-made structures in satellite images from around the globe. Denver, CO
********.*.*****@*****.***
github.com/gretchenriggs
linkedin.com/in/gretchenriggs
DATA SCIENCE & MACHINE LEARNING
Exploratory Data Analysis, Data Munging,
Web Scraping, Regression, Cross-Validation,
Regularization, Gradient Descent,
Hypothesis Testing, KNN, K-means
Clustering, Decision Trees, Random Forest,
Boosting, XGBoost, SVMs, Neural Networks,
Ensemble Methods, Principal Component
Analysis, AWS, Feature Learning,
Visualization, Anomaly Detection, Image
Processing
PROGRAMMING & ANALYSIS
Python (Pandas, NumPy, SciPy, scikit-learn,
statsmodels, matplotlib, seaborn), Keras,
TensorFlow, SQL/PostgreSQL, Jupyter
Notebook, Git, Github, Unix, C-shell scripting
Galvanize Data Science Curriculum
Statistical Inference, Regression, Supervised
and Unsupervised Learning, Graph Theory,
Recommendation Systems, Data
Visualization, Big Data Processing
Additional Coursework:
Coursera:
Stanford University
Certificate: Machine Learning
PyData:
Web Development for Data Science