Data Analyst for the Department of Institutional Effectiveness / Research

Functional experience working with retail and high-tech market leaders to support data, supply chain, business operations, and other cross functional teams through data strategy and analytic solutions.Experience as junior individual contributor, co-lead, and team player for various client-based and business development projects. Leadership practice with mentoring analysts and hosting knowledge transfer sessions regarding business case, documentation, and code bases.Accenture Data and AI Innovation Award 2023 recipientTechnical experience:Data science practitioner and developer for advanced analytic data workflows. Developed dashboards for key stakeholders and decision makers with curated analytics, KPIs, data quality metrics, business intelligent summary scorecards, and other innovative insight through Anaplan, Power BI, Python, SQL, and GCP applications.Demonstrated ability to leverage GCP products to architect and maintain data tables, workflows, Python and SQL scripts, and reporting dashboards. Experience with version controls technologies and code review processes.Demonstrated ability to leverage object-oriented programming, functional programming, software pattern designs, and unit testing with Python. Experience with version control technologies and code review process. Grew skills in Docker containers, LangChain, and LLM API development.Interests include data science, data engineering, generative AI, and responsible AI.

Graduate research assistantship providing statistical support for faculty research teams in the Department of Fashion, Interior Design, & Merchandising.Collaborated with teams to identify key drivers of garment insulation and correlate findings to biological thermal comfort and predict the insulation of new garment ensembles.Presented all primary statistical analytics, such as results of multiple linear regressions and One-way ANOVAs, and summarized findings for peer review. Utilized tools, such as Excel and Minitab, to clean, organize, manipulate, and analyze data.Published Article: “Utilization of An Infant Sweating Thermal Manikin to Determine Clo Values for Infant Clothing: A Comparison of Predictive Formulas (Journal: International Journal of Fashion Design, Technology and Education (TFDT))” (2021)

Predictive modeler internship with the Commercial Lines Actuarial Team. Co-collaborated to fine-tune Generalized Linear, LASSO, Ridge, and Elastic Net regression models to predict the frequency and severity of future claims.Utilized tools, such as MSSQL, Emblem, and R, to clean, organize, and manipulate data for training/testing statistical models.Presented statistical findings and methodologies to key internal stakeholders.

*** two-time summer intern ***Collaborated with the Engineering and Quality Departments on multiple continuous improvement projects to benefit key internal and external stakeholders.Applied DMAIC methodologies to reduce costs, improve cycle times, improve quality, and reduce waste.Reported data visualizations, exploratory analytics, and statistical analytics, such as linear regression and ANOVAs, for review.Utilized tools, such as, Excel and Minitab, to clean, organize, and manipulate data for data visiualizations, structured summaries, root cause analytics, design of experiments, and regression analytics.