Data Scientist for Perception Health tasked with optimizing performance of predictive modeling tools within the company's platforms.

• Developed Power BI visualization reports integrated with the company’s SQL server database for entire sales and marketing teams, providing data insights at multiple entry points along supply chain from distributor to end-consumer• Designed logistic regression models for predicting retailer product availability to circumvent the need for POS data• Automated AWS Lambda function for importing online orders to request review responses• Developed API using API Gateway/Lambda for unique customer landing page results using URL query string parameters• Provided guidance to key company stakeholders for processes of large-scale data collection through surveying and end-consumer communication platforms

• Designed and deployed AWS Lambda functions in Python for automated predictive modeling using stored, trained models. These reports integrated Lambda functions with S3 buckets for data extraction and storage, SES for automated notifications and API Gateway for triggering functions through external requests• Led and trained team of three developers in continued development of machine learning application. Trained the team on data analytic techniques in Python and AWS systems in order to equip the team for supporting independent analysis tasks• Worked with key company stakeholders to determine strategies for improvements to data collection and reporting.• Reported on weekly business KPIs

• Worked with experts in fashion industry to design and collect insightful data for predictive modeling. Identified key missing features needed for accurate predictions and initiated process for collecting these key features• Worked with database architects to improve collection of insightful data to be easily extracted for analysis and front-end applications• Designed supervised learning models using Python and Scikit-Learn for improved customer experience. This involved gathering proprietary data via SQL databases, performing feature scaling and encoding, selecting best fit models, pipelining standardization and hyperparameter optimization, training and testing models and storing trained models for future extraction. • Automated key performance indicators for steady and accurate business performance evaluation.

• Developed 40+ visualization reports through use of ETL processes and supported their continued use for the department to improve efficiency of daily engineering responsibilities. These reports were built through querying several relational databases with SQL, cleaning the data, then transforming the results using Excel, JMP, JSL, HTML and occasionally SSRS to provide practical data for driving daily decisions of the factory • Led a team of engineers in the wet etch area in support of ETL development• Supported Internet of Things team in pioneering development of their visualization reporting for tracking yield performance of products. This required extensive data cleansing and transformation in order to present reliable and accurate performance and trends. This "training" opportunity did not come with much direction, but rather open-ended requests to provide reports that the team did not have experience developing• Led module deep dive statistical analysis of excursion prevention monitoring systems to improve predictive systems of machine performance• Supported data systems report updates required as part of company migration of SQL databases from Oracle to DB2• Developed module cost trend tracking reports for cost reduction and sustaining efforts• As a department expert, trained all new hire engineers in department on the ETL process and and tool excursion prevention monitoring systems• Led weekly cross-site collaboration meeting to drive closure of projects to improve process quality and velocity• Led module investigations in support of 3 factory task forces, using data mining from large SQL database datasets, statistical analysis using JMP/JSL/Excel and MBPS to discover process marginalities and implement preventative actions• Led Kaizen event, overseeing team of 5 technicians and engineers, to improve engineering and technician task efficiency for the module

• Developed and supported automated data visualization reports using SQL/Excel/JMP/JSL/HTML to improve efficiency of daily engineering responsibilities• Used large datasets collected from SQL databases using SQL and analyzed using JMP/JSL/Excel to monitor and evaluate factory performance and quality• Reimagined data systems storage standards for module, implementing robust formatting for queries and documenting the new standards for all future support• Led module investigations in support of 5 factory task forces, using statistical analysis and MBPS to discover process marginalities and implement preventative actions• Used DOE, MBPS and statistical analysis to sustain and improve factory availability, velocity and product quality• Used statistical analysis techniques such as regression analysis to discover and mitigate process and equipment issues• Coordinated daily tasks for team of 5-10 technicians and junior engineers across 2 modules in the wet etch area in order to sustain factory output and availability• Supported technical training and upskilling for new technicians and engineers• Developed technical procedures for factory maintenance tasks

• Developed and maintained automated data visualization reports using SQL/Excel/JMP/JSL to improve efficiency of daily engineering responsibilities• Used DOE, MBPS and statistical analysis to sustain and improve factory availability and velocity and product quality• Coordinated daily tasks for 20-30 technicians across the 24/7 coverage team for the wet etch area.

• Prepared lab DOEs and instructed students weekly through completion of the DOEs• Organized and maintained examinations and assignments for upper level undergraduate electrical engineering course• Evaluated comprehension and completion of examinations and assignments for the course

• Used statistical analysis and white paper process to improve product quality by reducing variability captured by machine monitoring systems• Developed and maintained automated data visualization reports using SQL/Excel/JMP/JSL to improve efficiency of daily engineering responsibilities