Michael C. Email & Phone Number

Atlanta, Georgia, United States

Data aNd AI team (DNA)Main Languages for Development: Python and SQLFrameworks: Spark, Medallion Arch.Libraries: PySpark, Pandas, azure.storage.filedatalake, PyArrow, matplotlib, NumPy, sklearnAccomplishments in the DataBricks platform:- Engineered pipelines from scratch on application statistics sourced from MSFT Graph and Github apis.- Built out JIRA analytics that provide OpEx & CapEx expenditures, Ticket status and hourly analysis to NCR Voyix's board of directors.- Advanced United States Postal Services' dashboard by shifting their processes to utilize Azure Data Lake Stroage and Databricks workflow automations. Time saved customer ~2 hours daily from slow refreshes and prevented future memory problems in PBI.- Constructed a python notebook for Tableau usage statistics and monitoring. Saved DevOps Engineers about 3 hours of work of pulling and cleaning data for each data pull.Current Projects:- R&D on chat-bots leveraging Azure Open-AI.- R&D Retail, exploring LLM capabilities to help build customer's shopping list based on requests, feature, recipe, etc.- R&D Restaurant, Customer Personalization based customer's purchasing history (e.g. giving customer discount on a less busy day or time for their favorite item).- building out Azure ML space for HR Analytics projects.- finalizing dashboard for NCR Voyix's board of directors.- Implementing USPS's API to make the data more streamlined.- Maintaining HR Analytics platform and expertise.

Atlanta, Georgia, United States

I&T Data aNd AI (DNA)- Successfully split HR Synapse codebase, databases, and Workday APIs for the respective companies.- Led efforts to provide critical CE data for business reports that are shared with Wall Street investors.- Created metrics to monitor Pre and post split ADF and Synapse performance on the HR and Enterprise Azure subscriptions for both NCR Atleos and Voyix.- Continuously Engaged in Requirements analysis and gathering with HR business users.- Worked with Data Scientists to create an ML Model for HR Analytics use case.- Successfully moved a federal department's data ecosystem to Azure Databricks environment.Technical Achievements:- Created a DDL matching script in Python and SQL which reduced 75% of time spent in Excel manual data processing and improved DevOps analysis on DB health.- Contributed HR VM and Database analysis for overall cost savings on Azure Synapse and Azure Data Factory. Analysis contributed to Voyix DataOps' 880k savings on data platform costs.- Used Python to leverage Microsoft Graph API and map AD groups belonging to each unique AD User. On a quarterly basis, this saved a week's worth of manual prep and enabled quick analysis of AD users that need to be removed for cost savings. Primary libaries used were Pandas, JSON, & Request.

Atlanta, Georgia, United States

ITS - Enterprise Data Analytics (EDA):ERP Cloud On-Prem Migration for corporate finance team:• Created scripts in R (Libraries: dplyr, plyr, openxlsx, Dict) to semi-automate JIRA's bug export and NCR's banking manual files. Automation included reformatting the layout of Excel sheets, removing unnecessary characters, and matching primary keys to display SME names, areas of expertise, and ticket descriptions. • Created a JIRA dashboard via Excel and PowerBI that showcased 90% of closures of bugs and user stories on a weekly basis.• Set up a Google BigQuery database and connection to Mabl API; Worked with QA team to verify connectivity and data integrity.• Created Power BI dashboards to display Mabl live analytics for tracking progress (pass and failure rate, area of failure, etc.) of software test cases by each ITS team. • Deployed Mabl QA database saved approx. 20 hours monthly from manual Excel work and allowed managers to quickly identify an area that needed more support from the respective ERP dev teams.Analytics platform in Azure Synapse and splitting to NCR Voyix and NCR Atleos (NDA):• Performed "Lift and Shift" of business GitHub and SQL Server production code to Azure• Created an automated processes for extracting Data from Workday APIs; Data loads for weekly and monthly were reduced from several hours to just under an hour loading.• Elevated Database security by implementing SQL Masking based on AD user and group.• Developed data validation checks through SQL queries (EXCEPT command) and Python code (Libraries: Pandas, Pandera, JSON, OS)

Atlanta, Georgia, United States

Atlanta, Georgia, United States

Atlanta, Georgia, United States

Atlanta, Georgia, United States

Atlanta, Georgia, United States

Atlanta, Georgia, United States

Greater Atlanta Area

Atlanta, Georgia, United States

Master Of Science - Ms, Analytics

Path: Computational Data Analytics with a focus on AI and Machine Learning

Bachelor Of Business Administration - Bba, Actuarial Science And Risk Management

Activities and Societies: Actuarial Student Association (2020 - 2022) Indian Cultural Exchange (2021 - 2022) Dean's List (Spring 2019.

Education record

Activities and Societies: Division II Men's Cross Country (2016-2017)