Oliver Sherouse

Increased velocity by 16% and shifted performance from under-delivering to exceeding estimates through robust capacity planning and detailed ticket writing. Pioneered user-focused planning process that was adopted across the department to improve alignment with business goals.

Established and staffed a Data Engineering team of eight, providing professional and technical leadership. Spearheaded transition from a Go microservice architecture on Kubernetes to an AWS serverless architecture with no downtime.

Earned promotion at first review for above-level performance at defining and executing projects. Designed an analytics-focused data retrieval client in Python using Pandas, unblocking many projects for the Data Science team.

Modeled potential effects of free trade agreements for reports to Congress using Python, Pandas, and Statsmodels. Reviewed agency analysis of the effects of regulations on small businesses for quality of assumptions, statistical evidence, and economic reasoning.

Established and led a data science team of five, overseeing technical direction, hiring, training, and processes. Led development of QuantGov, an open-source Python-based framework for applying natural language processing and machine learning to policy documents.

Led technical development of an international well-being dataset, using Python and Pandas. Developed and presented a 'Python for Policy Analysis' course using Jupyter Notebooks, Pandas, Statsmodels, and Matplotlib.

Focused on public policy analysis and development. Gained expertise in policy formulation and implementation.

Studied a dual major in History and Computer Science. Developed strong analytical and problem-solving skills.