• Managed team of 5 data scientists and owned 7 applications and associated code bases as lead of the forecasting and reporting pod• Oversaw project to build self-service forecasting application and developed the front-end UI; the application allows users to submit forecasting requests for arbitrarily defined patient populations. In its first year of deployment, the application allowed us to increase our forecast volume by 120% annually • Defined and managed roadmap & prioritization for the pod and our products; aligned our strategic projects to the goals of the organization and the company as a whole• As a player-coach, responsible for setting the standard for clean & reusable code, building reliable products with robust testing suites, and software development and product management best practices

• Developed and maintained proprietary R package and associated infrastructure to automate data maintenance, processing, visualization, and asset population of 60-75 customizable monthly messaging campaign reports; leveraged ggplot and R’s data wrangling and visualization capabilities to automatically generate client-facing PowerPoint and Excel documents• Built multiple client-facing Shiny applications to apply and serve internally-developed machine learning models• Actively grew use of data visualization within the organization by developing Shiny applications for internal stakeholders to access and interact with underutilized data• Regularly and impactfully contributed to the team’s production-level code base in Python; assisted in designing and developing pipelines to automate and facilitate machine learning processes

• Leveraged all patient- and product-related data for various internal business initiatives, ranging from creation of models and dashboards to managing large, high-impact projects with many players throughout the organization, including valuing products and streamlining asset management processes through SQL and R • Designed and built new database infrastructure to more efficiently extract insights and report on client data• Led initiative to clean and update critical data with high business impact; interfaced with stakeholders throughout the organization to implement product changes to capture data in the most efficient way going forward, and created lasting infrastructure to ensure data integrity going forward

• Assisted in developing detailed documentation and specifications for client review, including policy documents and methodologies for calculating various government price types within the pharmaceutical industry• Acted as data lead for a large client engagement, responsible for building ETL to receive data, process, validate, and maintain all data in a secure SQL server, as part of the goal of redesigning and rebuilding the client’s data processes to ensure timely, accurate, and straightforward automated processes for submitting monthly and quarterly government price reporting requirements

• Analyzed Nielsen data to track and analyze performance of four of Discovery's networks: TLC, Investigation Discovery, The Hub, and Discovery Fit & Health• Conducted research using GfK MRI, Nielsen NPower, Star (MultiTrak), etc.