Danny Dietz

Conducted research and development in the AI space with specific emphasis on Microsoft Azure Open AI and Databricks. Implemented Databricks AI/BI Genie, cutting down tasks from a full workday to under an hour. Documented process flows to help stakeholders visualize AI Agents' capabilities and assist technical development resources.

Managed a team of 5-7 analysts focused on client data management and quality for approximately 100 clients. Designed dashboards to keep stakeholders aware of day-to-day data operations. Implemented processes in client onboarding, decreasing days clients spent in onboarding by approximately 50%.

Onboarded client data for over 20 clients. Standardized data, wrote requirements for ETL, and helped implement data management best practices. Monitored client data proactively for over 80 partners using SQL, Power BI, and Monday.com.

Handled large, complex SQL queries to help employees in the field quickly understand their clients’ quality scoring. Enhanced old reporting structures to make them more efficient and easier to debug.

Supported and trained on the enterprise reporting tool, IBM Cognos. Drove cross-functional knowledge sharing through the creation and administration of a business/data analyst community.

Translated business requirements to technical requirements for workflow management. Implemented SharePoint lists and workflows for large-scale projects across multiple operating companies. Helped ensure compliance to SDLC Waterfall methodology through training and administration of MS Project & Innotas.

Performed written translation of website and exhibit information for the organization. Contributed to making information accessible to a broader audience.

Completed a Master's degree focusing on decision analytics. The program provided advanced knowledge in data analysis and strategic decision-making.

Obtained a Bachelor of Science degree with a specialization in Economics. The curriculum covered economic principles and analytical methods.