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Spatial Data Jobs in Washington, DC (NOW HIRING)

Required : • Bachelor's degree in GIS or related field with 4-7 years of experience. • Experience with GIS software and spatial data analysis. • Develops geospatial applications and performs ...

Collect, clean, and process spatial data from various sources such as lidar, multibeam, remotely operated vehicle navigation systems, satellite imagery, GPS data, and public datasets * Conduct ...

Collect, clean, and process spatial data from various sources such as lidar, multibeam, remotely operated vehicle navigation systems, satellite imagery, GPS data, and public datasets * Conduct ...

Sr. GIS Solution Engineer- Health & Sciences

Vienna, VA · On-site

$55.50 - $71.50/hr

Be a technical leader of Esri technology as well as a subject matter expert of spatial data science. Demonstrate your advanced understanding of sales strategies and initiatives to develop complex ...

Collaborate with GIS staff to ensure accurate spatial data integration and assetmapping. * Manage vendor relationships and coordinate with Cityworks support for issueresolution and enhancements.

This role focuses on hands-on application development using JavaScript, TypeScript, ArcGIS Maps SDK for JavaScript, and modern web application frameworks to test ideas, visualize complex spatial data ...

Understanding of geospatial data formats, spatial data standards, and data management practices. . Familiarity with cloud-based GIS environments, preferably in AWS-heavy enterprise settings.

Showing results 41-60

Spatial Data information

See Washington, DC salary details

$50.4K

$146.9K

$201K

How much do spatial data jobs pay per year?

As of Aug 6, 2026, the average yearly pay for spatial data in Washington, DC is $146,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,700.00 and $155,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a spatial data analyst, and why are they important?

To excel as a Spatial Data Analyst, you need a strong background in geography, GIS, data analysis, and a relevant degree such as geography, environmental science, or computer science. Proficiency in GIS software (e.g., ArcGIS, QGIS), spatial databases (like PostGIS), and programming languages such as Python or R is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills distinguish top performers in this field. These competencies are essential for accurately interpreting spatial data, generating actionable insights, and effectively sharing findings with stakeholders.

What are some typical challenges faced by spatial data analysts when working with large geospatial datasets?

Spatial data analysts often encounter challenges related to data quality and integration when working with large geospatial datasets. Issues such as inconsistent data formats, missing metadata, and varying spatial resolutions can complicate analysis. Additionally, managing the computational load of processing and visualizing large, complex datasets may require specialized software and robust hardware. Collaborating closely with GIS specialists, IT teams, and data engineers helps to address these challenges and ensure reliable results.

What is the difference between Spatial Data vs GIS Analyst?

AspectSpatial DataGIS Analyst
Required CredentialsGIS certifications, degrees in geography, GIS, or related fieldsGIS certifications, degrees in geography, GIS, or related fields
Work EnvironmentData collection, database management, mapping softwareData analysis, map creation, spatial problem-solving
Employer & Industry UsageUsed by GIS professionals, urban planners, environmental agenciesEmployed in government, consulting firms, environmental organizations
Search & Comparison IntentUnderstanding data types, data managementAnalyzing spatial data, creating maps, reports

Spatial Data refers to the raw geographic information used in mapping and analysis, while a GIS Analyst actively interprets, analyzes, and visualizes this data to support decision-making. Both roles require similar credentials and are integral to GIS projects, but Spatial Data is the foundational information, whereas GIS Analysts focus on applying that data to solve spatial problems.

What is spatial data?

Spatial data, also known as geospatial data, refers to information about the physical location and shape of objects on Earth. This data is usually stored as coordinates and topology and can represent features such as buildings, roads, rivers, or even entire countries. Spatial data is used in mapping, geographic information systems (GIS), urban planning, environmental studies, and various other fields to analyze locations, patterns, and relationships. It can be stored in formats like vector (points, lines, polygons) or raster (grids, images). Understanding spatial data is essential for making informed decisions based on geographic information.
What are the most commonly searched types of Spatial Data jobs in Washington, DC? The most popular types of Spatial Data jobs in Washington, DC are:
What job categories do people searching Spatial Data jobs in Washington, DC look for? The top searched job categories for Spatial Data jobs in Washington, DC are:
Infographic showing various Spatial Data job openings in Washington, DC as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 8% Part Time, and 7% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $146,916 per year, or $70.6 per hour.

Senior Data Scientist (OBI Advanced Analytic Method Augmentation with Security Clearance

CELESTAR CORPORATION

Reston, VA • On-site

Other

Medical, Dental, Life, Retirement, PTO

Re-posted yesterday


Job description

Celestar Corporation is seeking a Senior Data Scientist (OBI Advanced Analytic Method Augmentation) to support The Defense Intelligence Agency ( DIA) under the Object Based Intelligence and Quality Assurance (OBIQUA) task order. The primary place of performance will be at DIA Facilities across the National Capital Region (NCR). If interested and meet the qualifications, we encourage you to apply for this rewarding and impactful opportunity. ANTICIPATED AWARD: TBD ANTICIPATED START: TBD PERIOD OF PERFORMANCE: 1 Base Year + 4 Option Years LOCATION: DIA Facilities across the National Capital Region (NCR) CLEARANCE REQUIREMENT: Active TS/SCI About Us: Celestar, a proud Veteran-Owned company, offers highly competitive salaries and benefits. Our comprehensive benefits package includes company-paid employee and family dental insurance, employee health insurance, life insurance, and disability coverage. Additionally, we provide a 401(k)-retirement plan with company matching, paid holidays, and personal time off. Responsibilities: This opportunity will support multiple DIA initiatives, including the Machine-Assisted Rapid-Repository System (MARS), Object Management Services (OMS), and Object-Based Intelligence (OBI). • The Senior Data Scientist (OBI Advanced Analytic Method Augmentation), Conducts data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions. • Proactively retrieves information from various sources, analyzes it for better understanding about the data set, and builds AI tools that automate certain processes. • Duties typically include: creating various ML-based tools or processes, such as recommendation engines or automated lead scoring systems. • Performs statistical analysis, applies data mining techniques, and builds high quality prediction systems. • Should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as Rand Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms. • Should have prior experience with large data multi-INT analytics, ML, and automated predictive analytics. • Designs, develops, and evaluates leading-edge algorithmic intelligence concepts, practices, and technologies for implementation into all-source analysis tradecraft, assessments, production, and dissemination. • Proposes advanced statistical or mathematical techniques and methodology that may permit identification and evaluation of alternatives, assists in model formulation or experimental test design, and shares jointly in team responsibility for development of advanced analytic techniques and assessments. • Evaluates data science, artificial intelligence, and other advanced analytic methods for risks, biases, and limitations that would distort conclusions. • Conducts continuous independent research on methods of analysis in government, industry, and academia to keep abreast of the state of the art, keeps senior leadership apprised of the advances and applicability to programs. • Utilizes in-depth knowledge of relevant theories, techniques, procedures and processes to investigate, prototype, and evaluate technologies to improve all-source intelligence analysis. • Provides technical input into and participates in the development of software and computer graphics systems. • Performs research studies to understand the process of augmenting or automating all source analytic processes using various computer models. • Provides incremental enhancements to tools, capabilities, processes, and methods. • Possesses in-depth knowledge and experience in using data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions. • Writes either R or Python scripts to drive data science workflows, have experience using SQL, and managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms. • Possesses prior experience with large data, spatial data, multi-INT analytics, ML, and automated predictive analytics. • Works with ambiguous information, deconstruct key questions, leverage spatial data, exploit application programming interfaces, suggest methodologies, develop data schemas to structure observations. This requires working knowledge of coding and scripting, information science, mathematics, machine learning, visual analytic modeling tools, and relevant Standard Operating Procedures (SOPs) to create repeatable, widely applicable procedures to support all-source intelligence analysis and production. • Creates and works in distributed analytic environments, scaling algorithms to work on increasingly large and complex datasets that are larger than RAM. • Serves as the primary POC for data science expertise, ensuring tradecraft compliance and analytic standards as it relates to data science techniques on the contract. • Provides advice on emerging data science methods, tools, algorithms, training, or requirements to advance DIA's analytic edge in its use of data science. • Works with DIA vendors and the software developers to implement distributed algorithms to work on increasingly large and complex data sets. • Review and evaluate OBI documentation submitted by advanced analytic (AA) owners to ensure compliance with tradecraft standards and adherence to best practices in AI system development and deployment. • Assess OBI documentation for completeness, accuracy, and thoroughness, and provide detailed feedback to owners and developers. • Provide consultation and guidance to data and AA owners, developers, and stakeholders on OBI governance and knowledge modeling, including best practices for system development, testing, and deployment. • Assist analytic methodologists and AA owners in translating technical documentation into analytic tradecraft compliant language. • Collaborate with stakeholders to develop, implement, and refine best practices for translating technical documentation into tradecraft compliant language • Review and edit translated documentation to ensure accuracy, completeness, and adherence to tradecraft standards. • Collaborate with the Computer Scientist to develop and implement testing methodologies for system validation and evaluation. • Conduct audits to ensure compliant use of systems for approved use-cases in all source analysis. • Develop and maintain a repository of audit findings and recommendations to facilitate knowledge sharing and best practices across the organization. • Design and execute TEVV protocols to evaluate the performance, robustness, and fairness of systems in all source analysis contexts. • Develop and apply statistical models and methods to analyze TEVV results and identify areas for improvement. • Collaborate with stakeholders to develop and implement corrective actions to address TEVV findings. • Develop and track performance metrics to evaluate the effectiveness of systems in all source analysis. • Analyze and interpret performance metrics to identify trends, patterns, and areas for improvement. • Collaborate with stakeholders to develop and implement data-driven decision-making processes to inform system development and improvement. • Develop and refine methodologies for evaluating system performance, robustness, and fairness in all source analysis contexts. • Collaborate with stakeholders to develop and implement best practices for system development, testing, and deployment. • Supports capability development by contributing, editing, and storing code in Government owned/controlled source version control repositories. Required qualifications/skills: • Minimum 12 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years with a master's degree. -OR- • A minimum of 17 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years with a bachelor's degree. • Must have at least 8 years of experience in AI implementation, advanced degree in computer science, data science, or related field. • Must have expertise in AI algorithms, model development, TEVV, and operationalization. • Possesses a professional or graduate certificate in data science from a university, major online learning platform (all business for Data Scientists at any experience level). • Demonstrates ability to work independently and with minimal oversight. • Active TS/SCI Clearance within the past 5 years. Come on board with a company that Values its Employees! Celestar Corporation is an Equal Opportunity Employer. The Celestar Corporation prohibits discrimination, harassment, and retaliation in employment based on race; color; religion; genetic information; national origin; sex (including same-sex); sexual orientation; gender identity; pregnancy, childbirth, or related medical conditions; age; disability or handicap; citizenship status; marital status; service member/protected veteran status; or any other category protected by federal, state, or local law.