Curriculum Vitae

Performance Profile

Proven data wrangler with knowledge in advanced statistical techniques and machine learning, with 10 years corporate research experience; planning and implementing data-driven solutions. Able to perform effectively in highly cooperative and collaborative team-oriented environments to solve enterprise, scientific, and engineering problems. Demonstrated ability to efficiently present research findings (verbally, visually, & interactively) to both technical and non-technical audiences.

Competences

Methods: Machine Learning, Data Science, Visualizations, Data Management, Hypothesis Testing, Experimental Design, & Applied Statistics
Languages: R, Python, SQL, Tableau, Matlab & SAS
Frameworks: Shiny, RMarkdown, Tidyverse, Docker, Pandas, Matplotlib & Scikit-Learn

Professional Experience

Data Scientist, Capture Higher Ed, Louisville, KY, 08/2018–Present
As a remote Data Science team member, I designed, deployed, and maintained partner-facing machine learning-based applications in R and Python on AWS. Advised partners on utilizing their tailored models to achieve higher education enrollment objectives and determine financial aid awards. Improved internal R packages for the Data Science Team through maintenance and enhancement efforts.

• Updated and modernized our containerized development environment with latest versions of R and Python, along with supporting ARM-based devices.

Data Scientist, Sandia National Laboratories, Albuquerque, NM, 07/2018–08/2022
Developed and productionized two machine learning models and four interactive data visualizations to improve safety, security, and employee retention. Provided ad-hoc data analysis to leadership on the performance of the $177.7 million Laboratory Directed Research & Development (LDRD) program. Collaborated with data engineers and software developers to increase the access and maintenance of 83 enterprise data sets. Established best practices in research software development by creating internal software packages and documenting CI/CD pipelines with Docker and GitLab.

• Co-leader of the five-person data visualization sub-team and technical leader of the four-person UI/UX data visualization style guide team.
• Developed three internally used R packages to simplify and standardize database connections, establish visualization standards, and package management.
• Proposed and awarded funding from the CIO to publish a data visualization style guide for use by the entire lab in public communications and professional journals. Currently being used by 28% of the Lab’s 14,000 workforce.
• Developed R Shiny web interfaces for machine learning predictive models to reduce the number of safety and security incidents.

Data Analyst, HID Global, Albuquerque, NM, 01/2012–06/2018
Managed the human testing lab; coordinated 53 research studies, in various sites in the US to evaluate biometric sensors. Analyzed resulting data to measure biometric sensor performance and prepare it for machine learning algorithms. Oversaw 12.89 terabytes of collected data. Presented research findings using various media (print, video, and webinars) to both technical and non-technical staff, and clients. Researched and identified new methods for spoofing biometric devices.

• Cut research study cost and product development time by improving subject recruitment; identified new recruitment methods, and improved communication that led to 48% subject retention rate.
• Engineered a data pipeline to process 3,000 videos from wireless security cameras collected daily throughout research sites in the United States for an object detection algorithm.
• Decreased algorithm development time and improved data quality by implementing new filename conventions, and creating a MATLAB accessible MySQL database to index collected data.
• Identified three unknown security threats to HID Global biometric sensors that lead to improvements in our fake finger detection algorithm.
• Collaborated with hardware engineers and computer scientists, on the research and development of four biometric sensors; including one for guests accessing the most visited vacation resort in the world.

Data Analyst, NMSU Department of Public Health Sciences, Las Cruces, NM, 08/2010–05/2011
While attending classes full-time, I actively assisted with a variety of health based research projects within the Department of Public Health Science. Provided statistical consulting to 8 graduate students and 11 faculty members at all stages of the research life cycle: grant writing, hypothesis development, survey and experiment design, preparing data, using statistical software to analyze data, and interpreting results for presentation or publication.

• This position was created specifically for me, after the department head was impressed by my knowledge of applied statistics, programming ability (in SAS and R), and communication skills.
• Authored a presentation with the university’s associate dean of research on using a new metric to measure sexual confront in college students.

Student Statistical Consultant, NMSU Department of Economics, Applied Statistics, and International Business, Las Cruces, NM , 08/2010–05/2011
Provided statistical support to graduate students and university staff by advising them on statistical analysis methods and software. Analyzed data with SAS and R. Worked on projects regarding: MBA admissions criteria, crime rates in motels, and dating websites.

Intern Statistician, USDA Food Safety Inspection Service, Washington, DC, 04/2010–08/2010
Ensured quality of raw data collected by the Food Safety and Inspection Service in meat, poultry, and processed egg product facilities throughout the United States. Cleaned raw data and updated data warehouse. Used statistical methodologies to estimate the prevalence of foodborne pathogens and prepared relevant figures for professional presentations.

• Authored a report for the public on the prevalence of pathogens in raw poultry products.
• Consulted with other interns from non-technical backgrounds on how to properly use statistical techniques on their work-related projects.

Education

MS in Applied Statistics, New Mexico State University, Las Cruces, NM, 2011

BS in Biology (Minor: Applied Math), New Mexico State University, Las Cruces, NM, 2009

Certification

Fundamentals of Computing by Rice University on Coursera. Certificate earned at July 7, 2018

Applied Data Science with Python by University of Michigan on Coursera. Certificate earned at September 28, 2017

Professional Training

Cloudera Data Scientist Training by Cloudera. 02/14/2022–02/17/2022

SAFe® Product Owner/Product Manager by Scaled Agile. 01/11/2022–01/13/2022

Storytelling with Data by Cole Nussbaumer Knaflic. 10/15/2020

JavaScript for Shiny Users at RStudio Conference 2020. 01/27/2020–01/28/2020

Apache Spark™ Programming (DB 105) by DataBricks. 09/24/2019

Presentations

Viz Wars: Tableau vs. Shiny, National Laboratories Information Technology Summit. Boise, Idaho. 04/29/2019

Assure for Safety, National Laboratories Information Technology Summit. Boise, Idaho. 04/28/2019

Conferences

RStudio Global Conference 2021 by RStudio, Virtual. 01/21/2021.

DOE Virtual Data Days 2020 by The Department of Energy, Virtual. 10/05/2020–10/07/2020.

Spark + AI 2020 Summit by DataBricks, Virtual. 6/22/2020

Conference on Data Analysis by Los Alamos National Laboratory, Santa Fe, NM. 02/25/2020–02/27/2020.

RStudio Conference 2020 by RStudio, San Francisco, CA. 01/29/2020–01/30/2020

National Laboratories Information Technology Summit by Federal Business Council, Inc. Boise, Idaho. 04/28/2019–04/31/2019