Where a GIS analyst's pay stops tracking map requests
$115,790estimated top of the range · middle $68,000 / yr
AI augments this role
GIS Analysts in the United States earn a median of $68,000 a year. Pay starts near $44,000. The top of the range is estimated at $115,790. The Bureau of Labor Statistics does not publish a separate wage series for this exact title, so this figure is derived from the closest occupation it does track and is labelled an estimate.
Source: PayCrunch estimate. Last checked 9 September 2026.
Entry level
$44,000
Top-end estimate
$115,790
Education
Bachelor's degree in GIS or Geography
Wages — PayCrunch estimate. The Bureau of Labor Statistics does not publish a separate wage series for GIS Analyst; figures are derived from the closest occupation it does track and are labelled as estimates. AI-impact rating is PayCrunch's editorial assessment. Updated September 2026.
🆕 New & Trending AI Tools for GIS AnalystReviewed September 2026
We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for GIS Analyst work right now.
Claude CodeNEWFree / usage-based
Terminal coding agent that reads your repo, runs tests, and ships multi-file changes.
How a GIS Analyst uses it: describe a feature and let it implement and test it across the codebase
OpenAI CodexNEWIncl. w/ ChatGPT plans
Agent that runs longer, deterministic multi-step coding jobs on its own.
How a GIS Analyst uses it: delegate a well-defined build or migration and review the finished result
WindsurfNEWFree / $15 mo
Agentic IDE that keeps context across a whole project.
How a GIS Analyst uses it: make large, coordinated changes without losing track of the codebase
AWS KiroNEWPreview / see site
Spec-driven coding agent that turns written specs into working code.
How a GIS Analyst uses it: write the spec first and let it build to that spec
NotebookLMNEWFree / $7.99 mo
Google tool that answers questions grounded only in the documents you give it — with citations.
How a GIS Analyst uses it: load your own manuals, policies, or PDFs and ask questions that stay accurate to the source
CursorFree / $20 mo
AI-native code editor that edits across an entire project.
How a GIS Analyst uses it: describe a change in plain English and let it rewrite and refactor whole files
GitHub Copilot (Agent Mode)$10–19 mo
AI pair-programmer built into VS Code and GitHub that now completes multi-step tasks.
How a GIS Analyst uses it: hand off a task and have it plan, edit multiple files, and open a pull request
ChatGPTFree / $20 mo
The most-used AI assistant — writing, analysis, research, and images from a plain-language chat.
How a GIS Analyst uses it: draft emails and documents, summarize long files, and get instant answers to on-the-job questions
ClaudeFree / $20 mo
AI assistant known for careful writing, long-document analysis, and coding.
How a GIS Analyst uses it: analyze big reports or spreadsheets and turn messy notes into clean, finished writing
A planning office with the layers already open
A GIS analyst spends the day making maps and keeping the layers under them honest. The usual seats are a city or county planning office, a regional planning body, an environmental consultant, a utility, or a public-works shop that has learned it cannot find its own pipes without a map. I supervise that kind of desk. The morning starts with a request: a planner needs a map for a public meeting, an environmental scientist needs parcels and habitat on the same sheet, or a department head wants to see where last year's permits landed. You are the person who turns that request into a picture and a short explanation.
Layers are the job's raw material. Parcels, zoning, streets, flood information, trails, wells, project boundaries, and whatever else the office has agreed to maintain. Your work is to know which layer is current, which one is a draft someone emailed, and which one would mislead a commission if you put it on the wall. You join information when the request needs it, and you stop when the join would pretend two datasets describe the same thing more cleanly than they do. I care less about a tour of software and more about whether you can say, in a sentence, what the map claims.
The week also includes maintenance nobody applauds. An address file drifts. A boundary changes. A consultant delivers a drawing that does not line up with the parcels. You fix what you can, you flag what you cannot, and you tell the person who owns the source data. Analysts who only make pretty maps and never repair the layers leave the next analyst a trap. Analysts who only repair layers and never deliver a map for Thursday's meeting leave the planner empty-handed. The job is both.
The request, the map, and the note
A good request is specific. Which place, which decision, which audience. You will not always get one. Part of the craft is turning "can you map this" into a boundary, a date, and a sentence about what the map is for. Then you build the view, check that the layers you used are the ones you meant, and write a note a non-specialist can read. The note says what is shown, what was left off, and what would change the picture. That note is how a planning director survives a public question without inventing an answer you did not give them.
Environmental offices use the same muscles on different layers. Wetlands, contamination boundaries, species habitat, sampling locations, and the project footprint have to sit together without false precision. You still write the note. A map that implies a clean edge where the data is fuzzy will be believed, and then it will be your problem. Say the limit on the map or beside it. Planners and scientists will respect a caveat they can repeat. They will not respect a beautiful sheet that collapses in the meeting.
You coordinate with people who do not live in the software. Planners, engineers, field staff, and clerks who maintain permits all feed you information and all need something back. The analysts I keep are the ones who answer in the planner's language and who keep a list of what they still owe. Heroic overnight maps are occasionally necessary. A reputation for them, and for nothing else, means the office has no process. Build the ordinary path: request, map, note, filed so the next person can find it.
City hall, a consultant desk, an environmental shop
Hiring managers look for a portfolio and a degree or a record that explains how you learned the work. Geography, planning, environmental science, and dedicated geospatial programs all appear. The credential is that training plus maps you can defend. There is no universal licence that makes someone a GIS analyst. Some public jobs sit inside civil-service titles that have their own rules. Some consulting jobs care only about whether you can produce under a deadline. Bring three maps: one for a public audience, one that combined layers carefully, and one where you had to say the data was not good enough. Walk through the decision, not every click.
In a city or county interview, expect a planner or an engineer on the panel. They will ask what you would do when two layers disagree and the meeting is tomorrow. Have a real answer from a real project: which source you trusted, who you called, what you labeled as uncertain. In a consulting interview, expect pace and client tone. Can you take a messy folder and return a sheet the project manager can send. In an environmental shop, expect comfort with scientific caution. The same person can win all three interviews with different examples. Using the flashiest map for every room is how you look interchangeable.
Say which office you want. A planning counter, a long environmental review, and a utility mapping group are different weeks. If you need to stay in one region, say that before they imagine a traveling crew. References should have received a map from you and used it. A professor can speak to training. A planner who presented your map in public can speak to trust. I hire the second reference when I have to choose.
Estimates, separate from geographer wages
The Bureau of Labor Statistics does not publish a separate wage series for a GIS analyst. These figures are PayCrunch estimates for this title. They are not geographer wages, and they are not state medians.
From the first layer to owning the conversation
You start by making the maps other people spec. The learning is local: where this office stores layers, who is allowed to edit them, and which planner will change the request twice. Do that work cleanly. Name files so a colleague can find them. Write the note even when nobody asked, and they will start asking. The analysts who skip the note create meetings. The analysts who write it create decisions.
The next step is owning a set of layers or a class of requests. You become the person who knows the parcel history, or the flood layers, or the way environmental constraints get drawn for reviews. People stop attaching a full tutorial to the email because you already know the office's rules. Some analysts then move toward a coordinator or manager seat and spend more time on requests, staffing, and the bargain with other departments about whose data is official. Some stay technical and become the person called when a join looks too perfect. Both are promotions if the pay and the respect follow. Ask which one your office actually means.
There is a middle stretch people skip in their own story. After you can make a correct map, the office starts trusting you with the layer itself: who may edit it, how often it is refreshed, and what happens when a department sends a spreadsheet that contradicts the map. That stretch is where analysts become hard to replace. It is quieter than a hearing-night map and more valuable. If your review never mentions it, ask for it. A career that is only emergency graphics stalls at the same tasks you were hired for.
Crossing from a city to a consultant, or from planning to an environmental firm, is common. Your portfolio has to be rebuilt in the new dialect. A commission map and a litigation-adjacent environmental figure do not impress the same reader. Keep samples you have the right to show. Strip client names when you must. And keep the habit that travels: a map, a caveat, and a note. Software will change. That habit is the career.
PayCrunch estimates, not a geographer series
PayCrunch built these figures because the Bureau of Labor Statistics does not publish a separate wage series for this exact title. Call them PayCrunch estimates. Do not call them geographer wages, and do not treat them as Occupational Employment and Wage Statistics for a GIS analyst. Entry is $44,000. The median estimate is $68,000. The gap from entry to the median is $24,000. The estimated top is $115,790. The gap from the median to that top is $47,790. No state median belongs in this conversation. If someone attaches any of these dollars to a state, they are adding a fact these estimates do not contain.
Use the three numbers as three different rungs. $44,000 is the entry estimate, a floor for a new analyst still learning an office's layers. $68,000 is the middle. $115,790 is the estimated top, the high figure in this PayCrunch range. The climb from entry to the median is $24,000. The climb from the median to the top is $47,790, a longer stretch. That shape means early raises and later senior talk are not the same size of conversation. A recruiter who opens at the top is describing the far end of an estimate. A recruiter who opens at $68,000 is describing the middle. Ask which one they intend.
Public salary schedules and consulting bands will not look like this estimate, and you can still lay them beside it. A city step that lands near $68,000 is an ordinary middle in this picture. A senior consulting rate that approaches $115,790 needs a reason: you own the layers, you face clients, you carry the deadline. An offer near $44,000 for someone who already runs the office's map requests is priced like a start. Say that with the $24,000 gap in view. Leave geographer medians out even if you hold a geography degree. The degree may be yours. These dollars are estimates for the analyst title, kept separate on purpose.
A short number set, used cleanly
Write the base on a line. Under it write $44,000, $68,000, and $115,790, and label them entry estimate, median estimate, and estimated top. Do not add a state. Then decide which gap you are standing in. New to the office, the $24,000 gap from entry to the median is the story of learning the layers and delivering maps people use. Established, with a portfolio and a set of layers you maintain, the talk starts at $68,000 and moves toward $115,790 only when the seat includes senior responsibility. The $47,790 gap is the upper room in the estimate. Pair it with the employer's schedule so you are not arguing from an estimate alone.
Negotiate the week beside the base. On-call map requests before public meetings, field time to check what the layer claims, and the unpaid role of teaching every new planner how to ask for a map all change the job. Ask who may edit official layers. Ask whether overtime or comp time exists when a hearing packet is due. Consulting offers should say whether you are billed out and whether that billing changes your pay. Get remote-work rules in writing if the layers live on a machine you cannot reach from home. Then come back to the three estimates so the salary has an anchor.
Before you accept, restate the work: maps, layers, and a planning or environmental office, with a note that says what the map means. Restate the pay as a PayCrunch estimate because the Bureau of Labor Statistics does not publish a separate wage series for this exact title. If the offer cites geographer wages, set them aside and return to $44,000, $68,000, and $115,790. The portfolio got you the interview. These three figures keep the money talk inside the right title. That is the whole discipline, and it is enough.
The top of GIS Analyst pay — and how to get there with AI
$115,790top-end estimate for GIS Analyst
PayCrunch estimate - derived from the closest occupation BLS tracks (Computer Occupations, All Other, 15-1299). This figure is PayCrunch’s estimate, not a Bureau of Labor Statistics published wage for this exact title.
And the role it leads to — Computer and Information Systems Managers — reaches $327,300 in Washington.
$44,000entry$68,000middle$115,790top end
Middle pay here goes to the analyst who answers each request as it lands; the top of the range goes to the one whose department cannot get through a week without the tool that analyst built and keeps running.
Requests arrive one at a time — a buffer, a service area, a layer for a council packet — and four of them are usually the same request wearing different clothes. Analysts who reach the top of the range build something that answers that request without them, which drags in the parts of this occupation that actually pay: verifying that the architecture stays interoperable and scalable once more people hit it, performing security analyses on the components you assembled, and training system users so the thing survives your holiday. Writing the code used to be the wall. With Cursor or GitHub Copilot open beside you, a script that reads a table out of Amazon Redshift and hands back a clipped layer is an afternoon, and your job becomes checking what it produced against a map you already trust.
Your playbook, by where you are now
Just startingTurn repeat requests into scripts
Log every request that reaches you for a month and mark the ones you have answered before.
Rewrite the three most repeated ones as scripts, using GitHub Copilot for boilerplate and comparing each result against a deliverable you produced by hand.
Learn the storage side well enough to pull straight from Amazon Redshift rather than waiting on somebody's extract.
Sit with one colleague who uses your output and watch where they get stuck; that is your first tool's specification.
Publish results as clean Adobe Acrobat exports so nobody has to open your project file to read a number.
What proves it: A script your team runs without you, with a written note on what it takes in and what it returns.
Realistic span: the first twelve to eighteen months
A few years inMake it a system someone maintains
Put the script behind a small internal page so requesters serve themselves instead of emailing you.
Run it on Amazon Elastic Compute Cloud EC2 so it does not die when your laptop closes.
Run a security analysis over every component you pulled in, then write down what you found and what you patched.
Test patches and fixes on a copy before they touch the live layer, and keep a record of what broke.
Train system users in a short session you repeat each quarter, then hand the notes to a colleague to deliver.
What proves it: An internal tool with named users, a change log, and a second person able to do maintenance on it.
Realistic span: years two through five
ExperiencedGet into the cost conversation
Join the meeting where project costs and design concepts get settled, and bring what your last three builds really took.
Write the guidelines installation teams follow for implementing secure systems, so security stops being re-argued every project.
Verify portability before a vendor is chosen: can the data leave, and what does leaving cost.
Take budget responsibility for one system end to end, which is the work that leads toward computer and information systems management.
California pays this occupation better than any other state; weigh that before you accept a local offer.
What proves it: A signed architecture or procurement recommendation a department acted on.
Realistic span: year six onward
The next 90 days
Over the next ninety days keep a plain list of every map or data request that reaches you, who asked, and how long it took. By the end of the first month the repeats will be obvious. Pick the one costing you the most hours and build the small thing that answers it — a script, a scheduled export, a self-serve page — and let an assistant draft the code so your hours go into checking output rather than typing it. Then do the part people skip: write half a page on how it works, sit down with the two colleagues who will use it, and train them properly. That is the line between an analyst who fills requests and one a department has to plan around.
Wage figures: PayCrunch estimate. The playbook is PayCrunch editorial guidance, not a guarantee of pay or placement.
Every figure is the national median from the U.S. Bureau of Labor Statistics (OEWS) shown on that role’s own page.
Never used AI before? Start here (2 minutes).
Start with the AI assistant already inside your GIS. Esri now ships AI assistants in ArcGIS Pro and ArcGIS Online that write Arcade expressions, build geoprocessing workflows, and answer 'how do I' in plain language — turn them on and use them on a real task this week. If you're on QGIS, pair it with ChatGPT or Claude to write PyQGIS and GDAL commands.
The single biggest force multiplier is letting AI write your Python — ArcPy, GeoPandas, rasterio — so batch jobs that took a day take minutes. Learn free with Esri's ArcGIS tutorials, the QGIS training manual, and Google Earth Engine's docs; when a script breaks, paste the error into the AI and have it explain and fix it. Keep sensitive coordinates out of public tools (see the safety rule).
The one rule, forever: Location data is powerful and sensitive — never expose personally identifiable or protected locations (homes, sensitive sites, tribal or conservation data) in public AI tools, and always verify AI-generated coordinates, projections, and analysis against ground truth. A wrong datum, CRS, or hallucinated result can send crews to the wrong place; you are responsible for spatial accuracy, not the model.
The plays — exact steps, exact prompts
Do these in order. Each one is copy-paste ready. You do not need to know anything about AI going in.
1
Automate geoprocessing with AI-written Python
Why this pays: The gap between a $68,000 map-maker and a $98k analyst is automation. An analyst who scripts repetitive workflows delivers many times the output and takes on modeling work — AI writing your ArcPy and GeoPandas is the fastest way to cross that gap.
ChatGPTArcGIS Pro (ArcPy)GeoPandas
1
Identify a repetitive task (clip-project-buffer-summarize across many files) and have ChatGPT or Claude write the ArcPy or GeoPandas script to batch it.
2
Generate a working geoprocessing script from a plain description.
Copy-paste this prompt
Write a Python script using GeoPandas that reads all shapefiles in a folder, reprojects them to EPSG:[3857], buffers each by [500 meters], performs a spatial join with [census_tracts.shp] to attach population, and exports a summary CSV of population within each buffer. Handle CRS mismatches explicitly and add comments.
Always confirm the CRS and datum and spot-check results against a known area — a wrong projection silently corrupts everything.
3
Save these as reusable script tools or ArcGIS toolboxes so the whole team (and future you) runs them in one click.
What you'll haveBatch automation that turns day-long workflows into minutes — the productivity and modeling capacity that pays $98,000.
2
Do remote sensing and imagery analysis at scale
Why this pays: Remote sensing and Earth observation are among the highest-paid GIS specialties. AI cloud platforms and segmentation models let one analyst analyze continent-scale imagery — a rare, well-paid skill that lifts you to the top of the band.
Google Earth EnginegeemapSegment Anything (SAM)
1
Use Google Earth Engine (with the geemap Python library) to run change detection, NDVI, or classification across large areas without downloading a single scene.
2
Write the Earth Engine analysis with AI.
Copy-paste this prompt
Write a Google Earth Engine Python (geemap) script to compute annual NDVI change for [county or AOI bounding box] between [2020] and [2025] using Sentinel-2, mask clouds, export a GeoTIFF, and plot mean NDVI per year. Explain each masking step.
Validate cloud masking and date ranges; verify a few pixels against known land cover before trusting the map.
3
Use segmentation models like Segment Anything (or Esri's deep-learning tools) to extract features — buildings, water, fields — from imagery instead of digitizing by hand.
What you'll haveContinent-scale imagery analysis on demand — a high-value specialty that commands top-of-range GIS pay.
3
Build decision-grade dashboards and spatial models
Why this pays: Analysts get paid for decisions, not layers. Whoever builds the dashboard or suitability model leadership actually uses becomes indispensable — AI speeds the build so you produce more decision tools, the visible value that earns raises and the senior title.
Build interactive ArcGIS Dashboards (or Experience Builder) on live data, using the AI assistant to write the Arcade expressions for symbology, pop-ups, and indicators.
2
Design a suitability or weighted-overlay model from a plain-English goal.
Copy-paste this prompt
I need a site-suitability model for [siting EV chargers / new clinics] in [area]. Given layers [population, road network, existing sites, zoning, income], propose a weighted-overlay methodology: which layers, how to normalize each, suggested weights with reasoning, and the ArcGIS Pro tools and steps to run it. Note the key assumptions I should document.
Use as a methodology draft — you must justify weights and validate outputs; a suitability model is only as good as its assumptions.
3
Wrap the analysis in a short narrative (StoryMaps) so non-GIS stakeholders act on it.
What you'll haveDecision tools leadership relies on — the visible, high-value work that drives promotion to senior-analyst pay.
4
Turn analysis into clear narrative and reporting
Why this pays: The analyst who communicates — not just computes — gets pulled into higher-visibility, better-paid roles. AI drafts the methodology write-ups and stakeholder summaries so your work lands and gets funded.
ClaudeArcGIS StoryMapsChatGPT
1
Draft the methodology and plain-language findings for a mixed audience.
Copy-paste this prompt
I ran a [flood-risk] analysis using [method and layers]. Write two versions of the results: (1) a technical methodology section for the report appendix with data sources, steps, and limitations, and (2) a 150-word plain-English summary for [city council] that states the finding, the confidence, and the recommended action.
Verify every number and caveat — AI will smooth over uncertainty you need to keep visible.
2
Assemble the visual story in ArcGIS StoryMaps so the map, method, and recommendation travel together.
3
Reuse the structure as a template for future analyses to standardize your team's reporting.
What you'll haveAnalysis that decision-makers understand and act on — the communication edge that opens senior and lead roles.
5
Credential and specialize into a high-pay domain
Why this pays: GIS pay tops out by specialty — utilities, transportation, environmental, remote sensing — and by credentials (GISP, Python). AI accelerates the learning so you specialize faster, and specialists sit at the $98k end of the band.
ChatGPTEsri TrainingNotebookLM
1
Pick a high-value domain and build a study plan.
Copy-paste this prompt
Act as a GIS career mentor. I want to specialize in [electric-utility GIS / hydrology and flood modeling / remote sensing]. Build a 90-day plan: the core spatial concepts and datasets to master, the specific ArcGIS/QGIS/Python skills, 3 portfolio projects that prove the skill, and any certifications (GISP, Esri, domain-specific) worth pursuing.
Use to structure learning; build real portfolio projects with public data to prove it.
2
Load dense manuals and standards into NotebookLM and quiz yourself to master a domain's data models fast.
3
Publish a portfolio project (web map plus write-up) in your target domain to signal the specialty to employers.
What you'll haveA paid specialty and credentials that place you firmly in the top of the range for GIS earners.
Your 12-month sequence to the top of the range
How the plays above stack into a path from median pay toward the $98,000 tier.
Month 1
Turn on the ArcGIS AI assistant (or pair QGIS with ChatGPT) and automate one repetitive workflow with AI-written Python.
Months 2-3
Build a library of reusable script tools; add Earth Engine and imagery analysis to your skill set.
Months 3-6
Ship a decision-grade dashboard or suitability model that a stakeholder actually uses.
Months 6-9
Sharpen communication — StoryMaps and clear methodology reporting — and pick a specialty.
Months 9-12
Pursue a credential (GISP, Python, or domain) and publish a portfolio project in your specialty.
Gear for this job
As an Amazon Associate, PayCrunch earns from qualifying purchases. Links to books and tools are for the job on this page; we only recommend what we’d use in the work.
Eider Press 2022 (ISBN 978-0-97176-475-0) for the Esri ArcGIS / GISP play. Not the GISCI handbook. Not Esri Academy. No leftover GISP card.
Next steps for a GIS Analyst
Some links below are affiliate or partner links. PayCrunch may earn a commission if you enroll or subscribe through them, at no extra cost to you. Wage figures on this page still come from the Bureau of Labor Statistics, not from these programs.
GIS Analyst work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Computer Occupations, All Other (SOC 15-1299). O*NET Job Zone 4 is typical: a bachelor's degree, so the honest next credential is a professional certificate or bachelor's-level coursework — not a random catalog dump.
The occupation's listed knowledge area is Geography, which is what the course searches below actually query.
GIS Analysts in this dataset list AJAX among the tools in use, so a program that names that stack is a better fit than a survey course.
Coursera search for geography — a professional certificate or bachelor's-level coursework that lines up with computing, not a generic professional-development aisle.
FlexJobs screens remote, hybrid, freelance, and flexible listings so you are not wading through unverified ads. This is a job-board search for GIS Analyst work, not a claim that they list a counted SOC 15-1299 inventory.
Write a GIS Analyst resume, or one aimed at Computer and Information Systems Managers, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.
A GIS Analyst resume that names the actual tasks on this page, or the step-up title Computer and Information Systems Managers, beats a blank template when you apply.
What GIS Analysts earn by state
This page does not show a state table, and the reason is worth stating: the Bureau of Labor Statistics does not publish a separate wage series for this job title, so there are no official state figures to show. Scaling the national median by a cost-of-living index would produce a number for every state, but it would be an estimate of living costs wearing a wage’s clothes, and PayCrunch would rather show you nothing than that.
What the national figures say: pay starts near $44,000, the median is $68,000, and the top of the range is $115,790. Those national figures are a PayCrunch estimate, not a Bureau of Labor Statistics published wage for this exact title.
No, but it raises the bar. AI automates the digitizing, scripting, and basic mapping that used to fill an analyst's day. What it can't do is frame the right spatial question, choose and justify a methodology, validate results against ground truth, and translate a map into a decision. Analysts who move up into modeling and spatial data science are more valuable; those who only make basic maps are the most exposed.
Do I need to become a programmer to stay competitive?
You need to be able to read and direct code, not necessarily write it from scratch. AI writes most of your ArcPy, GeoPandas, and Earth Engine now — but you must understand what it produces, verify projections and results, and debug it. Analysts who can drive Python with AI leave button-pushers far behind on pay.
Is it safe to use ChatGPT with my organization's spatial data?
Not with sensitive or identifiable locations. Never paste protected coordinates — homes, sensitive sites, tribal or restricted data — into public tools. Use AI for code, methodology, and general questions, and keep confidential geodata inside your approved systems. Always verify AI output against known ground truth.
Which AI skill gives a GIS analyst the biggest pay bump?
Automating workflows with AI-written Python, closely followed by imagery analysis at scale with Google Earth Engine. Together they move you from producing maps to producing models and decisions — the work that separates $98,000 analysts from the median.
ArcGIS or QGIS — does it matter for using AI?
Both work. ArcGIS now has built-in AI assistants and deep-learning tools; QGIS pairs cleanly with ChatGPT or Claude for PyQGIS and GDAL. Employer demand often favors ArcGIS, but the transferable, high-value skill is scripting and spatial modeling with AI regardless of platform.
Methodology & sources
Salary (median, 10th, top of the range) — U.S. Bureau of Labor Statistics, OEWS.
By state — the Bureau of Labor Statistics’ own state medians, limited to states employing at least 500 people in the occupation. No cost-of-living arithmetic is applied to a wage anywhere on this page.
The plays — PayCrunch's own step-by-step guidance using publicly available AI tools. Tool names/URLs are real and current as of August 2026; prompts written to work as-is. Verify any professional output before relying on it.