Geospatial Analyst IV

prosidian is a management and operations consulting services firm focusing on providing value to clients through tailored solutions based on industry leading practices. Prosidian services focus on the broad spectrum of risk management, compliance, business process, it effectiveness, energy & sustainability, and talent management. We help forward thinking clients solve problems and improve operations.
launched by former big 4 management consultants; our multidisciplinary teams bring together the talents of nearly 190 professionals nationally to complete a wide variety of engagements for private companies, fortune 1,000 enterprises, and government agencies of all sizes. Our services are deployed across the enterprise, target drivers of economic profit (growth, margin and efficiency), and are aligned at the intersections of assets, processes, policies and people delivering value.
prosidian clients represent a broad spectrum of industries to include but are not limited to energy, manufacturing, chemical, retail, healthcare, telecommunications, hospitality, pharmaceuticals, banking & financial services, transportation, federal and state government agencies. Learn more about prosidian consulting at

provide expertise to plan, coordinate, and execute geospatial data collection, processing and analytical services in support of research and operational applications. Leads geospatial data science teams in the application of remote sensing/geospatial technologies, approaches and methodologies to address natural resource applications including change detection, monitoring, extraction and classification of information from multispectral imagery, radar, lidar, etc. Use supervised/unsupervised image classification, data mining and feature extraction technologies, accuracy assessment procedures, and identify and apply novel approaches to geospatial analysis and modeling.

master’s degree related to geography, geographic information systems, remote sensing, or physical / biological / environment / natural resource discipline with substantive coursework in geospatial analysis and modeling, and seven (7) years of relevant professional work experience in geospatial analysis and modeling.

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phd degree related to geography, gis, remote sensing, or physical / biological / environmental discipline, including emphasis or coursework in geospatial analysis and modeling, and five (5) years of relevant professional work experience in geospatial analysis and modeling.

core competencies

• teamwork – ability to foster teamwork collaboratively as a participant, and effectively as a team leader
• leadership – ability to guide and lead colleagues on projects and initiatives
• business acumen – understanding and insight into how organizations perform, including business processes, data, systems, and people
• communication – ability to effectively communicate to stakeholders of all levels orally and in writing
• motivation – persistent in pursuit of quality and optimal client and company solutions
• agility – ability to quickly understand and transition between different projects, concepts, initiatives, or work streams
• judgment – exercises prudence and insight in decision-making process while mindful of other stakeholders and long‑term ramifications
• organization – ability to manage projects and activity, and prioritize tasks

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other requirements

• business tools – understanding and proficiency with business tools and technology, including microsoft office. The ideal candidate is advanced with excel, access, outlook, power point and word, and proficient with adobe acrobat, data analytic tools, and visio with the ability to quickly learn other tools as necessary.
• commitment – to work with smart, interesting people with diverse backgrounds to solve the biggest challenges across private, public and social sectors
• curiosity – the ideal candidate exhibits an inquisitive nature and the ability to question the status quo among a community of people they enjoy and teams that work well together
• humility – exhibits grace in success and failure while doing meaningful work where…