Lead development of centralized data platform to store historical data from past leadership, team, and organization assessments. This data includes reports, interviews, organizational redesigns, and personality assessment data, which is then used as the foundation for research, new product development, and enhanced reporting. Act as principal source and subject matter expert of production data reporting and analysis by providing data project management, leading data team growth and development, participating in data strategy setting and long-term planning, and managing and supporting relationships with data and technology service providers.• Created table structure, database structure, unique key system in Splunk Cloud for previously completely unstructured data from 8+ sources• Led Data Security compliance initiative after determining there was a critical need for improvements to our company policies (and enforcement of those policies) and data practices • Developed custom GenAI agent in currently beta-phase GenAI product after testing various Generative AI platforms. Learned prompt engineering and agent definition best-practices to create a Summit-specific agent designed to emulate our consulting and reporting. The agent is in ongoing development, but has already been able to save consultants an average of 2 hours of writing per report• Scalability scorecard analysis and creation: Used feature analysis and clustering to identify what characteristics make a leader “scalable” in their role as their company grows. Used feature engineering to group variables into overall dimensions, then compared variable distributions to determine best ranges for leader scorecard. Leaders qualifying for all categories showed 27% more effectiveness on average than leaders that didn't meet criteria• Set data strategy and created roadmap: Participated in strategy formation sessions, contributing expertise to feasibility of projects and timelines for 2024-2025 project roadmap

Applied data science solutions to recruiting and human capital data to create forecasts, predictions, summaries, and data stories. Projects included building machine learning applications in RShiny, Python Dash, and Streamlit, developing data flows, dashboards, and data visualizations in Oracle Analytics Cloud, and providing data insights and stories to internal leadership and external clients. Used both R and Python for analytics projects including XGBoost models, decision trees, clustering analyses, data manipulation and feature engineering, k-Means clustering, and custom score and metric development. Additional work included building a strong data foundation to support all projects by assisting in data validation and organization in Oracle SQL Developer and Oracle Analytics Cloud. Developed advanced analytics capabilities at Personify through project development with direct interaction with stakeholders at all levels of leadership, acting as an internal data analytics consultant, and additionally providing educational presentations on analytics and data visualization principles to entire organization.• Developed and deployed dashboards to entire organization to track performance metrics • Developed and productionalized random forest model to forecast work volume for Client Services team, leading to more effective employee management and preparation for bottlenecks• Through research and working with employees across all levels of the company determined a major bottleneck in the candidate sourcing workflow and developed a work prioritization system to reduce time spent on each requisition and keep up with new inventory

Credit Score Expansion Scorecard ML Model: Used industry data to create a XGBoost machine learning model in R to identify risk-splitting variables in each credit score tier. The goal of the project was to expand lending at lower credit bands by better identifying risk in those customers. The XGBoost model was tuned through a hyperparameter matrix, and ultimately was able to predict whether an applicant would go delinquent with above 90% accuracy. Once variable importance was established decision trees were used to determine optimal variable splitting points of risk in order to create a customer scorecard.Adverse Selection Machine Learning Model: Built a machine learning model in R comparing industry and PenFed specific customers to determine where PenFed was being adversely selected for loans by car dealerships.Regional Risk Premium Analysis: Conducted a risk analysis through univariate and bivariate analyses on a specific region that has high industry risk and determined that PenFed customers in that region showed significantly lower risk than the rest of the industry. This allowed for an alignment in policy between that region and the rest of the United States, expanding available customer base in that region through loans being made available to a lower credit tier, leading to a projected 5% growth in portfolio.Third-Party Information Provider Value Analysis: Was key information provider on decision on whether to use a third-party vehicle and customer information provider’s scores on vehicle loan applications. Analyzed the projected value of the provider to determine whether using their loan scores would provide an increase in value. Used swap-in-swap-out variable analysis to determine that their proposed scores would be extremely conservative and limit the available portfolio greatly, reducing profit while increasing expense through paying for the service.

Used knowledge of information and data tracking systems, as well as data manipulation, to validate all data records from the past four years between the Birst data tracking system and the Microsoft Excel records. These records had been full of user-entry errors, but with my team I was able to validate these records to approximately 98% accuracy. Quickly gained an intimate working understanding of the intricacies of the dual systems to tie out the records.Developed powerful statistical visualizations for use by various members of Personify to view information that was not being analyzed or displayed anywhere else. This included building a dashboard to track employee performance, which was then used to display sales leaders as a motivational tool. Additionally constructed a significantly more in-depth financial review dashboard for the CEO and division leaders in the company. This included projections of sales for the year, as well as compared actual performance throughout the year versus the performance goal. I consult with division managers to develop statistics, visualizations, and dashboards to review the performance of the divisions at Personify.

Worked to build a communicative relationship with student-athletes by developing methods of communication and instruction and assisting them in their learning experience.

Coordinated the plan and execution of multiple festivals and events such as the Rogallo Kite Festival and the SUPTastic Paddleboard race. Responsible for the overall planning for SUPTastic, such as safety, transportation, trophies, and other details of the event. Planned and designed promotions for Hatteras Island tourism such as activity discounts for a major campground in Rodanthe, NC which led to both an increase in rentals and the opportunity to build a strong relationship with that campground, leading to more marketing opportunities.

Assumed responsibility for the safety and satisfaction of groups of customers, sized 2-15. Made decisions pertaining to the instructional program and development of the customer’s skills through both on-boat instruction and coaching from another boat.