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Remote Lidar Data Processing Jobs in California (NOW HIRING)

Survey Crew Chief

San Diego, CA · On-site +1

$43.30 - $56/hr

... lidar sensors, and magnetometers. * Plans and executes aerial imagery and remote sensing data ... Analyzes and processes survey data for accuracy, completeness, and compliance with regulatory and ...

Survey Crew Chief

San Diego, CA · On-site +1

$43.30 - $56/hr

... lidar sensors, and magnetometers. * Plans and executes aerial imagery and remote sensing data ... Analyzes and processes survey data for accuracy, completeness, and compliance with regulatory and ...

REMOTE - US Residents Only  We are looking for a thorough and analytical Data Analyst to go with our present team. Your job in this role will mostly consist on data collecting, processing ...

Showing results 41-60

Remote Lidar Data Processing information

What is remote lidar data processing?

Remote LiDAR data processing involves handling and analyzing LiDAR (Light Detection and Ranging) data from a location other than where the data was collected. Professionals use specialized software to process large datasets, extract features like terrain models or vegetation, and generate 2D or 3D representations of landscapes. This remote work setup allows teams to collaborate globally, efficiently process data for industries like mapping, forestry, and urban planning, and deliver results without being physically present at the survey site.

What are the key skills and qualifications needed to thrive in remote lidar data processing?

To thrive as a Remote Lidar Data Processing Specialist, you need a solid background in geospatial sciences, data analysis, and remote sensing, often supported by a relevant degree such as geography, GIS, or engineering. Familiarity with specialized software like LAStools, ArcGIS, and Global Mapper, as well as experience with data formats such as LAS and point cloud processing, is typically required. Strong problem-solving skills, attention to detail, and effective communication are essential soft skills for ensuring data accuracy and collaborating with team members. These skills and qualifications are important because they enable precise data interpretation, efficient workflow, and the delivery of high-quality geospatial products to clients.

What are some common challenges faced in remote lidar data processing, and how can they be overcome?

Professionals working in remote Lidar data processing often encounter challenges such as managing large datasets, ensuring data accuracy, and troubleshooting software or hardware compatibility issues. Effective organization and use of cloud-based storage solutions can help handle large volumes of data efficiently. Additionally, staying up-to-date with the latest processing software and regularly participating in team meetings or online forums can aid in resolving technical problems and maintaining data quality. Proactive communication with team members also ensures smooth collaboration, even in a remote work setting.

What is the difference between Remote Lidar Data Processing vs Remote GIS Analyst?

AspectRemote Lidar Data ProcessingRemote GIS Analyst
Required CredentialsTypically requires GIS or remote sensing certifications, technical skills in lidar softwareRequires GIS certifications, spatial analysis skills, and often a degree in geography or related field
Work EnvironmentPrimarily technical, focused on lidar data handling and processing softwareMore analytical, involving spatial data analysis, mapping, and reporting
Industry UsageUsed in surveying, mapping, environmental monitoring, infrastructure planningApplied in urban planning, environmental management, resource allocation

Remote Lidar Data Processing focuses on handling and analyzing lidar point cloud data, while Remote GIS Analysts interpret spatial data for decision-making. Both roles require GIS knowledge but differ in technical focus and application areas.

What are the most commonly searched types of Lidar Data Processing jobs in California?

The most popular types of Lidar Data Processing jobs in California are:

What are popular job titles related to Remote Lidar Data Processing jobs in California?

For Remote Lidar Data Processing jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Lidar Data Processing jobs in California look for?

The top searched job categories for Remote Lidar Data Processing jobs in California are:

What cities in California are hiring for Remote Lidar Data Processing jobs?

Cities in California with the most Remote Lidar Data Processing job openings:

Real Estate Data Scientist - Remote

Harbor Freight Tools

Calabasas, CA • On-site, Remote

$98K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 25 days ago


Job description

The Real Estate Data Scientist is responsible for developing advanced analytical models and data-driven tools that support strategic real estate decisions across the organization. This role partners closely with Real Estate, Finance, Marketing, and Supply Chain teams to deliver predictive insights related to site selection, network optimization, sales forecasting, and market planning. This role incorporates advanced spatial modeling, geostatistics, and geospatial data engineering to evaluate trade areas, quantify market potential, and optimize network performance.
This position combines strong statistical modeling, data engineering, and business acumen to translate complex data into actionable recommendations. The Real Estate Data Scientist plays a critical role in advancing the organization's use of machine learning, automation, and predictive analytics to improve decision quality and scalability. This is a senior individual contributor role with no direct people management responsibility.
Duties and Responsibilities
  • Advanced Analytics & Predictive Modeling
    • Develop and deploy predictive models for site selection, sales forecasting, cannibalization, and market potential.
    • Build and maintain machine learning models using regression, classification, clustering, optimization, and spatial modeling techniques.
    • Apply spatial statistical methods (e.g., spatial regression, geographically weighted regression, spatial autocorrelation) to capture geographic variation in demand drivers.
    • Develop trade area and customer draw models (e.g., Huff/gravity models) to estimate market share and competitive impact.
    • Incorporate spatial features such as proximity, co-tenancy, demographics, traffic patterns, and nearby store performance into predictive models.
    • Design methodologies for forecasting store performance under various scenarios, including spatial and competitive effects.
    • Continuously monitor and improve model performance and accuracy. 
  • Data Engineering & Automation
    • Design scalable data pipelines integrating real estate, customer, demographic, sales, and geospatial datasets (parcel, census, traffic, mobility, POI data).
    • Perform geospatial data processing including geocoding, spatial joins, coordinate transformations, and spatial indexing (e.g., H3 or similar frameworks).
    • Write efficient SQL and Python workflows to automate recurring analyses, spatial feature engineering, and model refreshes.
    • Ensure data quality, consistency, and reproducibility across analytical outputs, including alignment of spatial boundaries and geographic hierarchies.
  • Real Estate Strategy & Decision Support
    • Partner with Real Estate teams to support site selection, market entry, relocations, and closures.
    • Develop drive-time and network-based trade area analyses to assess accessibility and market reach.
    • Conduct market coverage and white space analysis to identify expansion opportunities and underserved areas.
    • Build location-allocation and network optimization models to determine optimal site placement.
    • Quantify cannibalization and competitive effects using spatial overlap and proximity-based modeling.
    • Provide quantitative insights for Real Estate Committee (REC) evaluations and executive decisions.
    • Develop scoring frameworks and decision tools to prioritize opportunities.         
  • Visualization & Communication
    • Create clear, compelling visualizations and dashboards (Tableau, Power BI, or similar) to communicate insights.
    • Develop interactive geospatial visualizations including trade area maps, performance heatmaps, and market opportunity analyses.
    • Present analytical findings and recommendations to senior leadership and non-technical stakeholders.
  • Experimentation & Innovation
    • Design and execute experiments (A/B tests, quasi-experimental designs) to evaluate real estate strategies.
    • Implement geo-based testing frameworks (e.g., test vs. control markets) to measure impact of site decisions.
    • Apply causal inference methods (e.g., difference-in-differences, synthetic control) accounting for geographic spillovers.
    • Explore new data sources (e.g., mobility, foot traffic) and modeling techniques to enhance predictive capabilities.
    • Contribute to building a best-in-class real estate analytics capability.
  • Cross-Functional Collaboration
    • Work closely with GIS, Data Engineering, Finance, Marketing, and IT teams to align data and models.
    • Partner with GIS teams to ensure alignment between spatial analysis, mapping, and production data pipelines.
    • Translate business problems into analytical solutions and actionable insights.
Scope
  • Staff supervision and development:  No
  • Decision making: 
    • Develops models and analytical frameworks used in strategic decision-making
  • Travel:  Up to 10%
  • Flex Designation:  Anywhere

The anticipated salary range for this position is $98,500-$147,800 depending on location, knowledge, skills, education and experience. This position is also eligible for an annual discretionary bonus. In addition, we offer comprehensive and competitive benefits to Associates (and their families) such as medical, dental, vision, life insurance, short-term and long-term disability. Eligible Associates are able to enroll in our company's 401k plan. Associates will accrue paid time off up to 236 hours per year (inclusive of PTO, floating holidays, and paid holidays). Paid sick time up to 80 hours per year unless otherwise required by law.