Shannon Proctor Email & Phone Number

San Diego, California, United States

• Leveraged by command leadership as organizational subject matter expert for data science initiatives.• Hand selected for highly visible team focused on enterprise-wide digital transformation.• Automated data integration pipelines across organizational boundaries ensuring consistent, accurate, and timely data to enable data driven decisions at the speed of relevancy.• Introduced and integrated Agile development framework methodologies for cross-division and command project teams, implementing frequent small feature releases with consistent customer engagement.• Designed, developed, and implemented an automated Procurement Dashboard in Power BI Cloud Service, recognized as the enterprise gold standard.• Self-taught, developed a Power Apps solution for community leaders to enter engagement data, track trends and internally manage personnel while providing mechanism for clean, consistent data collection.• Pioneered organization implementation of Robotic Process Automation (RPA) solution to automate repetitive data tasks. • Executed from inception to delivery, the development of an enterprise Wellness Readiness Dashboard in Qlik, spanning six disparate wellness domains and giving leadership a holistic view of the Health of the Force.

Irvine, California, United States

• Involved in end-to-end data efforts supporting multi-year, $25M National Institute of Mental Health initiative to address the effect of early-life adversity on brain maturation.• Leveraged R to create models, run simulations, and produce analytics products for animal and human research.• Managed (stored, cleaned, documented, analyzed) long-term video imaging data for multiple cohorts.• Consulted and supported other efforts in planning statistical analyses, developing innovative risk models, data management support, and subject matter expertise.

Irvine, California, United States

• Led individual tutoring, group lessons, and discussion sessions on topics including exploratory data analysis, data visualization, linear regression, analysis of variance, simulation, and optimization methods, serving 60+ students per class for 2 courses: Biological Statistics and Introduction to Probability for Computer Science.• Trained students how to write human and machine-readable code using R.• Introduced and taught the utilization of R to write human and machine-readable code for data analysis.• Taught concepts such as study design, simulation, random variables, Bayesian estimators, and frequentist hypothesis testing in the context of computer science and data literacy.

Bs Applied Statistics

Concentration: Neurobiology Data Analytics Intern, National Cancer Institute (2014)

Phd Coursework

Ms Statistics

Concentration: Biostatistics (Clinical Studies, Neurobiology, Epidemiology)