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Gis Machine Learning Jobs in Washington, DC (NOW HIRING)

GRVTY

Geospatial Analyst - Mid

Falls Church, VA

$85K - $105K/yr

Implement technical knowledge of GA tradecraft including GIS analyses such as: * Viewshed / Line of ... Experience working with or developing Machine Learning algorithms for exploiting overhead imagery ...

GRVTY

Geospatial Analyst - Mid

Falls Church, VA · On-site

$85K - $105K/yr

Implement technical knowledge of GA tradecraft including GIS analyses such as: * Viewshed / Line of ... Experience working with or developing Machine Learning algorithms for exploiting overhead imagery ...

Unissant

Senior Data Scientist

Washington, DC · On-site

$130 - $150/hr

Work Experience and Job Skills * 10+ years of experience in data science, machine learning, or ... Proficiency with geospatial tools (ArcGIS, GIS platforms) and BI tools (Qlik, Tableau, Power BI ...

Esri

Federal Account Manager - Public Sector

Vienna, VA · On-site

$104K - $187K/yr

... GIS, you will apply your selling skills to address a huge transformation in technological capabilities across the public sector that includes Artificial Intelligence (AI) and Machine Learning (ML ...

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All JobsGis Machine Learning JobsGis Machine Learning Jobs in Washington, DC

Gis Machine Learning information

See Washington, DC salary details

$16

$32

$54

How much do gis machine learning jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for gis machine learning in Washington, DC is $32.31, according to ZipRecruiter salary data. Most workers in this role earn between $24.52 and $38.12 per hour, depending on experience, location, and employer.

What is a GIS Machine Learning job?

GIS Machine Learning jobs involve applying machine learning techniques to geographic information systems (GIS) data to analyze spatial patterns, make predictions, and solve complex geospatial problems. Professionals in this field use algorithms and models to process location-based data, automate mapping tasks, and extract insights from satellite imagery or sensor data. These roles often require skills in programming, data analysis, and an understanding of both GIS principles and machine learning methodologies. GIS Machine Learning specialists can work in industries like urban planning, environmental monitoring, agriculture, and disaster management.

What are common challenges when integrating machine learning models with GIS data, and how can they be addressed?

One common challenge in GIS machine learning roles is handling the complexity and diversity of spatial data, which often comes in various formats and resolutions. Ensuring data quality and alignment is crucial, as inconsistencies can negatively impact model performance. Another challenge is computational efficiency, since spatial datasets can be very large. Collaboration with data engineers and GIS analysts is often necessary to preprocess data effectively and optimize workflows. Staying updated with advancements in geospatial libraries and cloud-based solutions can help address these challenges.

What are the key skills and qualifications needed to thrive as a GIS Machine Learning specialist, and why are they important?

To thrive as a GIS Machine Learning Specialist, you need expertise in geospatial analysis, machine learning algorithms, and a background in GIS-related fields, often supported by a relevant degree. Familiarity with tools like ArcGIS, QGIS, Python, R, and libraries such as scikit-learn and TensorFlow, as well as experience with spatial databases, is crucial. Strong problem-solving, critical thinking, and effective communication skills help translate complex data into actionable insights. These abilities enable professionals to develop innovative geospatial solutions and drive informed decision-making in diverse sectors.

What is the difference between Gis Machine Learning vs GIS Analyst?

AspectGis Machine LearningGIS Analyst
Required CredentialsBachelor's in GIS, Computer Science, or related; knowledge of machine learningBachelor's in Geography, GIS, or related; GIS certifications often preferred
Work EnvironmentData science teams, software development, research projectsUrban planning, environmental agencies, government offices
Employer & Industry UsageTech companies, research institutions, environmental firmsGovernment agencies, consulting firms, urban planning departments
Common Search & Comparison IntentUnderstanding technical skills and data modelingAnalyzing spatial data for projects and reports

Gis Machine Learning focuses on applying machine learning techniques to spatial data, often requiring programming and data science skills. In contrast, GIS Analysts primarily work with spatial data analysis, mapping, and reporting within various industries. While both roles involve GIS, Gis Machine Learning emphasizes advanced data modeling, whereas GIS Analysts focus on spatial data management and visualization.

What are popular job titles related to Gis Machine Learning jobs in Washington, DC?

For Gis Machine Learning jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Gis Machine Learning jobs in Washington, DC look for?

The top searched job categories for Gis Machine Learning jobs in Washington, DC are:

Gis Machine Learning jobs near you

Data Scientist (Mid) - TS/SCI

Wiser (Tennessee)

Springfield, VA

Full-time

Re-posted 19 days ago

Job description

Data Scientist - TS/SCI Cleared

Location: Springfield, VA

Required Clearance: Top Secret/SCI Security Clearance

Wiser offers innovative solutions to clients in the public, private, and government sectors. We combine technology and expertise to develop inventive solutions that deliver quality results and aid in critical decision making. With the flexibility and efficiency of a small business, we provide nimble responsiveness with the low risk and strong performance experience of an established GEOINT and Geospatial service provider.

Required:

  • U.S. Citizen
  • Active Top-Secret/SCI security clearance at time of application and willingness to complete a CI poly upon request.
  • A total of 5 points of relevant background via one of the following pathways:
    • High school diploma and 5 years of relevant military or relevant professional experience. 
    • Relevant Bachelor's degree and 2 years of relevant experience.
    • Relevant Bachelor's degree and relevant Master's degree. 
  • Firm grasp of programming skills with the ability to write / maintain scripts, including Python and JAVA scripts and familiarity of querying with SQL.
  • Knowledgeable in data science, including the areas of data services, modeling, and analytics.
  • Knowledgeable of geospatial data management including data type conversion; coordinate systems (latitude and longitude, UTM) and their conversions; and knowledge of projections and their properties / conversions.
  • Prior experience working with data quality control tools including ArcGIS Data ReViewer.
  • Knowledge of ESRI Workflow Manager WMX and TAM.

Preferred:

  • Preferred experience with artificial intelligence, natural language processing, machine-to-machine learning, and NoSQL including document and graph schemas, ontologies, OWL, and data base inferencing. 
  • Experience with combining digital cartography, computer technology, GIS, cartographic and geospatial production techniques, remote sensing, photogrammetry, and digital data formats.
  • Ability to clean / prune data to discard irrelevant information
  • Ability to examine data from a variety of angles to determine hidden value, weaknesses, trends, and/or opportunities
  • Advanced knowledge of ESRI ArcGIS and ArcServer
  • Knowledge of database systems and architecture (ORACLE, PostgresEQL, NoSEL (MongoDB), Microsoft Access)
  • Ability writing SQL (and NoSQL for senior candidates)
  • Understanding cloud architecture, infrastructure, services (including geospatial specific microservices), and DevOps
  • Knowledge of symbolization rules (how symbols are used to portray features)
  • Knowledge of generalization rules
  • Experience working with geospatial data in a multi-user enterprise environment (i.e., versioning data)
  • Knowledge of artificial intelligence, natural language processing, and machine-to-machine learning
  • Knowledge of Metrics dissemination
  • Ability to convert unstructured data into structured data
  • Proficient in MS Outlook, Word, PowerPoint, Access, and Excel
  • Senior candidates may have additional knowledge of Data Warehousing, Data Mining, Predictive Modeling, Data Integrity / Security, Data Anomaly Detection, Statistical Analysis, S-57 data structure, specifications, validation, and the ability to produce ENC and AML, use of ECDIS display systems

Work Environment

Work is within a team environment and will be conducted 50% telework and 50% on site in Springfield, VA. 

*Candidates are encouraged to submit a resume that explicitly addresses each of the requirements listed above.

Wiser Imagery Services employs personnel within the states of Alabama, Florida, Georgia, Illinois, Indiana, Maryland, Missouri, North Carolina, North Dakota, Ohio, Pennsylvania, Tennessee, Texas, Virginia, and West Virginia.

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

To comply with Federal law, Wiser Imagery Services participates in E-Verify. Successful candidates must pass the E-Verify process upon hire.

Wiser Imagery Services is a drug-free workplace.

We respectfully request not to be contacted by recruiters and/or staffing agencies.

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