• Utilizing programming techniques to produce understandable and usable datasets, tables, and reports from various data sources driven by project specific needs.• Performing exploratory data analyses to visualize, quantify, describe, and validate data fields for analytical purposes.• Managing, monitoring, and maintaining SAS datasets and SQL Server tables used by the Data Analytics department as well as supporting complex data requests.• Organizing complex clinical and operational data from multiple sources in support of the development of meaningful and impactful reports and data products for contract deliverables and special research.• Developing, managing, and documenting project-specific analytic datasets and analytics data marts. • Responding to complex requests from internal and external requestors for data analyses and reports that require advanced programming methods, with discussion and interpretation of the results.

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● Managed the remediation of software and system vulnerabilities with 95% conformity to timing regulations by employing data analytics software, JIRA, and other remediation tools● Decreased the incidence of vulnerability escalation in our systems by approximately 90% over the course of one year (2021) by maintaining metrics to identify trends in vulnerability remediation and informing management and collaborative teams● Formulated and crafted a new procedure to address the remediation of a specific group of vulnerabilities, allowing for a reduction in the volume of outstanding unresolved vulnerabilities● Coordinated the completion of compliance projects with other internal Wells Fargo teams by leading productive meetings, following up on assigned activities, and completing all deliverables● Coordinated the systematic decommissioning of 200 servers by ensuring that all required protocols were delivered and all intermediate tasks were completed within the required timeframes, averting non-compliance● Assigned and distributed one-off tasks and activities to other team members based on skill sets and availability in order to increase the productivity of the team by 20% in terms of tasks completed per week

• Developed and conceptualized a regression model and calibration study with the aid of SAS and SQL software to accurately predict channel infiltration in the Walnut Gulch Experimental Watershed (WGEW)

• Decreased the cycle time of a crucial annual analysis by a factor of ten by employing SAS data integration software to fill in missing identification information for a population of over 500,000 taxpayers• Analyzed and processed the results of 16 recurring customer satisfaction surveys by utilizing statistical analyses performed in SAS and SQL to discern trends and track taxpayers’ satisfaction over time, thereby providing data-based feedback to customer service agents and leading to performance improvements• Created dynamic SAS and SQL programs, implementing data pulls and data joins, which allowed efficient, repeatable programming for all recurring analyses• Employed SAS data mining techniques (cluster analysis, decision trees, neural networks) to identify the characteristics of taxpayers who would be most likely to self-correct underreported income errors• Developed and implemented visual displays, graphics, charts, and tables for inclusion in reports and verbal presentations with the aid of SAS visualization software and Microsoft Excel

• Developed a regression model to predict channel infiltration in the Walnut Gulch Experimental Watershed for implementation in the National Water Model, and presented this research at the AGU Fall Conference 2017 • Conceptualized and executed a calibration study on runoff data from the Walnut Gulch Experimental Watershed using the KINEROS/AGWA water model to confirm the aforementioned infiltration estimates • Scholarly paper “Comparison between Observed and Simulated Channel Network Infiltration Losses in a Semi-Arid Catchment” to be published Summer 2018

• Developed process improvements that led to a 25% decrease in cycle times for several products • Collaborated with safety personnel to implement safer procedures in the manufacturing facility for handling large quantities of raw materials• Monitored process parameters on a daily basis to identify and correct process problems

• Streamlined the overall glass-making process and ultimately eliminated 20% of the cycle time by implementing effective Statistical Process Control procedures• Utilized statistical software packages and databases to develop and implement process improvements with a high purity glass-making process• Designed experiments and conducted gage R&R studies to validate and improve processes and to implement new measurement devices• Developed practical data metrics and displays for use by plant operations group, ultimately demonstrating a 40% yield improvement within the process• Developed and managed technical documentation for manufacturing processes