This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Westwood Professional Services, Inc. is seeking a Senior Remote Sensing Technician to join our team. The Senior Remote Sensing Technician is responsible for post-processing aerial data to final deliverables supporting multiple markets and users. This role involves ensuring the accuracy and reliability of all deliverables created from LiDAR and imagery data from both manned and unmanned aircraft, troubleshooting technical issues, and conducting quality control checks. The Senior Remote Sensing Technician will work closely with Remote Sensing Project Leads and other stakeholders to support the successful execution of projects. Qualifications - Minimum 5+ years of experience or Associate degree or equivalent in a related field (e.g., geomatics, surveying, remote sensing). - Minimum 3+ years in a senior technician role. - ASPRS certifications highly desired. - Strong understanding of LiDAR and remote sensing principles and data processing. - Proficiency in using Remote Sensing software and tools, such as TerraSolid, RiProcess, MicroStation, MetaShape, Photoshop, PLS-CADD, TopoDOT. - In-depth knowledge of coordinate systems and projections. - Industry experience in power generation and delivery, DOT, and renewables. - Scripting and light programming knowledge to support automation. - Familiarity with surveying techniques and equipment for project control understanding. - Excellent problem-solving and troubleshooting skills. - Strong attention to detail and ability to work with precision. - Effective communication and teamwork skills. - Ability to work independently and manage multiple tasks simultaneously. - Willingness to adapt to changing technologies and industry trends. Requirements - Work closely with Remote Sensing Leadership and Project Leads to meet project expectations. - Perform post-processing procedures according to internal guidelines and industry best practices. - Create final deliverables based on project scope for various markets ready for the client as final deliverables. - Troubleshoot technical issues related to aerial datasets. - Conduct thorough quality control checks to ensure the accuracy and reliability from junior technicians. - Stay updated on the latest advancements and best practices in remote sensing. - Assist in the development and implementation of standard operating procedures for aerial deliverables. - Collaborate with software vendors to address issues and obtain necessary support. - Participate in training programs and workshops to enhance technical knowledge and skills. - Assist with testing and implementation of new software. Company Description At Westwood, our purpose is to create a better world for people through our work. We transform the energy grid, design resilient infrastructure, and develop communities that will flourish today and for future generations. With over 50 years of experience and a legacy of innovation, we stand at the forefront of our industry, dedicated to understanding the unique needs of the markets we serve. Join us in creating a better world. - In 2024, Zweig Group ranked Westwood nationally at #13 and #40, respectively, on its Hot Firms and Best Firms to Work for lists. - Zweig also awarded Westwood one national 1st place award for Marketing Excellence. - Westwood was recently recognized as #83 in the ENR Top 500 Firms in 2024. - The firm consistently ranks on the industry's top 25 lists and receives recognition for its involvement in award-winning projects nationwide.

• Design, build, and maintain the data models, dashboards, and reporting frameworks that give the commercial organisation clear, trusted visibility across the full commercial funnel • Use AI tools as a core part of your analytical workflow — accelerating insight generation, improving output quality, and freeing up capacity for higher-order problem solving • Run deep-dive analytical projects to surface patterns, anomalies, and opportunities in commercial data, translating findings into clear and actionable recommendations for commercial stakeholders • Define and track KPIs that measure both business outcomes and the effectiveness of the processes driving them, creating a continuous improvement feedback loop • Own preparation and follow-through for key internal meetings, strategic reviews, and cross-functional forums — ensuring the right data is in the room and decisions translate into clear next steps • Build the analytical frameworks that underpin quarterly planning, forecasting, and target-setting, producing outputs commercial leaders can use directly • Map, challenge, and rebuild core commercial workflows — including pipeline management, forecasting cadences, and sales incentive structures — into cleaner, faster, and more scalable ways of working • Implement operational improvements end-to-end: not just designing the solution, but driving adoption and measuring impact with rigour • Identify where AI can fundamentally change how commercial processes work, then build and deploy those solutions directly • Develop a hands-on understanding of our commercial tech stack, diagnosing where friction, data loss, or missed opportunities exist • Translate commercial problems into well-defined briefs that Product and Engineering teams can act on, bringing enough technical fluency to be a genuine peer in those conversations

• Design, build, and maintain the data models, dashboards, and reporting frameworks that give the commercial organisation clear, trusted visibility across the full commercial funnel • Use AI tools as a core part of your analytical workflow — accelerating insight generation, improving output quality, and freeing up capacity for higher-order problem solving • Run deep-dive analytical projects to surface patterns, anomalies, and opportunities in commercial data, translating findings into clear and actionable recommendations for commercial stakeholders • Define and track KPIs that measure both business outcomes and the effectiveness of the processes driving them, creating a continuous improvement feedback loop • Own preparation and follow-through for key internal meetings, strategic reviews, and cross-functional forums — ensuring the right data is in the room and decisions translate into clear next steps • Build the analytical frameworks that underpin quarterly planning, forecasting, and target-setting, producing outputs commercial leaders can use directly • Map, challenge, and rebuild core commercial workflows — including pipeline management, forecasting cadences, and sales incentive structures — into cleaner, faster, and more scalable ways of working • Implement operational improvements end-to-end: not just designing the solution, but driving adoption and measuring impact with rigour • Identify where AI can fundamentally change how commercial processes work, then build and deploy those solutions directly • Develop a hands-on understanding of our commercial tech stack, diagnosing where friction, data loss, or missed opportunities exist • Translate commercial problems into well-defined briefs that Product and Engineering teams can act on, bringing enough technical fluency to be a genuine peer in those conversations

• Design, build, and maintain the data models, dashboards, and reporting frameworks that give the commercial organisation clear, trusted visibility across the full commercial funnel • Use AI tools as a core part of your analytical workflow — accelerating insight generation, improving output quality, and freeing up capacity for higher-order problem solving • Run deep-dive analytical projects to surface patterns, anomalies, and opportunities in commercial data, translating findings into clear and actionable recommendations for commercial stakeholders • Define and track KPIs that measure both business outcomes and the effectiveness of the processes driving them, creating a continuous improvement feedback loop • Own preparation and follow-through for key internal meetings, strategic reviews, and cross-functional forums — ensuring the right data is in the room and decisions translate into clear next steps • Build the analytical frameworks that underpin quarterly planning, forecasting, and target-setting, producing outputs commercial leaders can use directly • Map, challenge, and rebuild core commercial workflows — including pipeline management, forecasting cadences, and sales incentive structures — into cleaner, faster, and more scalable ways of working • Implement operational improvements end-to-end: not just designing the solution, but driving adoption and measuring impact with rigour • Identify where AI can fundamentally change how commercial processes work, then build and deploy those solutions directly • Develop a hands-on understanding of our commercial tech stack, diagnosing where friction, data loss, or missed opportunities exist • Translate commercial problems into well-defined briefs that Product and Engineering teams can act on, bringing enough technical fluency to be a genuine peer in those conversations