This document summarizes the skills and experience of an individual with extensive experience in machine learning, data science, and applied mathematics. They have strong proficiency in Python, machine learning algorithms, deep learning, AWS, and data visualization. Their experience includes managing large data analysis projects, designing statistical experiments, and clearly communicating technical topics. They have leadership roles in human rights and engineering communities.

1. Proficient in Python (including
standard data science libraries
such as pandas, matplotlib
scikit-learn, scipy, and numpy),
Jupyter Notebooks
Experience with Tensorflow,
Apache Spark, Git, AWS,
Linux, and SQL
Skilled in data visualization
Theoretical and practical
understanding of most
supervised and unsupervised
machine learning models and
algorithms, advanced
understanding of statistics
Intermediate knowledge of deep
learning architectures, signal
processing, and time series
analysis
Exceptional ability to
communicate technical material
Experience with project
management
Software and Tools
Mathematics and Modeling
Leadership/Communication
SKILLS
Moscow Human Rights
Commission, Board Member
Humanists of the Palouse,
President and Board Member
Frequent panelist, speaker, and
mentor for local Women in
Engineering events
COMMUNITY
INVOLVEMENT
Phone: 208-577-0175
Email: cassienseubert@gmail.com
LinkedIn: @cassie-seubert
Moscow, Idaho
CONTACT DETAILS
EXPERIENCE
Extensive experience using machine learning, statistical analysis, and other applied
mathematical techniques to solve difficult power systems problems. Consistent use of
statistical reasoning to identify appropriate model parameters for algorithm deployment
in large-scale data analysis.
Theoretical and practical proficiency in constructing and implementing data pipelines to
extract explainable features and build machine learning models that identify power
system signatures. Experience using Tensorflow with Keras to identify signatures from
raw time series data.
Demonstrated ability to use AWS EC2 instances to analyze large datasets and implement
distributed, parallel processing on terabytes of data stored in S3.
Experience using software engineering principles to write testable code and employ
source control using an Agile workflow.
Exceptional aptitude for designing and implementing controlled statistical experiments.
Notably, planned and carried out an experiment assessing the effectiveness of specific
manufacturing processes. Results lead to a savings of over $1 million and an order of
magnitude increase of efficiency.
Technical Experience
CASSIE
SEUBERT
Data Scientist
Leadership, Communication, and Project Management Experience
Principal investigator on an $875,000 Department of Energy contract with academic sub-
awardees. To date, have successfully managed project within budget and met all project
deliverables and milestones.
Considerable experience writing customer facing reports that require clear
communication of technical material.
Comfortable presenting to large audiences, including composing and communicating
technical presentations in an engaging and understandable way.
Passionate about teaching and helping guide others to understanding.
Proven ability to handle sensitive material as a holder of a TS SCI government clearance.
WORK HISTORY
Research Engineer
Schweitzer Engineering Laboratories | 2017 - Present
Lead Quality Analyst
Schweitzer Engineering Laboratories | 2012 - 2017
ACADEMIC HISTORY
Research emphasis on error detecting and correcting codes
Participated in undergraduate research at UCLA modeling plant growth in the Santa
Monica mountains
MS Mathematics, GPA 4.0
Washington State University | 2014 - 2017
BA Mathematics, Minor Psychology, GPA 3.92, Summa Cum Laude
University of Southern California | 2008 - 2012