Steven Rothstein

In this role, I focus on analytics for a patient-centric app and platform. My role is to build connections, storage, and visualizations for data across over 30 different systems. In addition to writing the code, I liaise across the department and enterprise to build scalable solutions that meet the needs of the business. More specifically, I have built custom libraries consisting of thousands of lines of code to read and write from various databases and flat files, as well as to connect to multiple APIs through HTTP methods. These libraries are also used to clean and format data using scalable solutions so that we optimize the time needed for data analysis without sacrificing on the quality and level of detail of the analysis. These analyses are ultimately built and presented within Tableau.

Developed automated Java programs to integrate with a third-party system, log transactions to a Microsoft SQL Server database, and export data directly to Excel. Identified an automation pipeline between two systems via PHP APIs and designed an interface to reduce manual data entry.

Conceived, developed, and implemented an automated, data-driven Java product analysis framework from scratch, resulting in higher-quality products and expedited time to market. Built and maintained a KPI metrics dashboard that was consumed directly by the Chief Operating Officer. Led cross-functional teams to champion products from inception through post-production monitoring; regularly identified bugs / data issues; coordinated with business and technical units to remediate prior to implementation. Executed or oversaw the QA testing for over 300 software changes within approximately a one-year period, in turn contributing to significantly improved software products and increased customer satisfaction. Defined and prioritized both technical and business requirements due to deep knowledge of IT systems and business processes; supported project managers in scope definition and time, resource, and work effort estimates. Led testing and reported results directly to executive management for a successful project that saved the company $56 million in risk adjustment payments and was completed in a compressed timeframe.