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This role involves researching trends, executing marketing campaigns, collaborating across teams, and developing GIS expertise within Infrastructure industries.

Work with customers to define problems and design ML solutions; build and deploy predictive models (feature engineering, model selection, HPO) for big and streaming data; write clean, version-controlled code; apply geospatial ML best practices; create data visualizations and communicate results to non-technical stakeholders; stay current with machine and deep learning advances.

Design, test, and release ArcGIS Online components across cloud infrastructures (AWS, Azure, VMware). Implement and validate backend APIs and security features, create and run manual and automated tests, troubleshoot customer issues, collaborate cross-functionally, and produce technical documentation and content.

The specialist will lead campaigns targeting Infrastructure industries, collaborate with various teams, and develop GIS domain expertise to support marketing efforts and customer engagement.

Develop front-end applications using JavaScript/TypeScript and Python-based geoprocessing tools. Collaborate with cross-functional teams, apply object-oriented design, follow software methodologies, and deliver GIS-focused solutions using Esri products and APIs.

Lead strategy and execution of integrated marketing campaigns for the state and local government market. Create content, manage events, run analytics, collaborate with partners, and build community to drive revenue and market presence.

As a Senior Product Manager for ArcGIS Online, lead idea intake, enhance decision clarity, and ensure alignment between teams while improving product governance and operational rhythms.

The Sr. Change Management Specialist will ensure successful adoption of internal marketing projects, develop change management strategies, and foster employee engagement through effective communication and training.

Develop scalable and efficient geocoding algorithms and APIs while optimizing C++ code for performance and memory consumption. Collaborate with engineers on geocoding solutions.

The role involves designing and developing AI-driven software to improve geospatial data quality. Responsibilities include developing ML components, collaborating with cross-functional teams, and integrating AI algorithms for product releases.