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The conservation scientist who brings the money in

$134,350top of the range in Colorado · middle $73,010 / yr
AI augments this role

Conservation Scientists in the United States earn a median of $73,010 a year. Pay starts near $47,550. Pay reaches $134,350 at the top of the range in Colorado, the best-paying state for this work among those with at least 500 people in the job.

Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Conservation Scientists, SOC 19-1031). Last checked 9 September 2026.

Entry level
$47,550
Top of the range · Colorado
$134,350
Education
Bachelor's degree in Environmental Science
Lower disruption Higher exposure AI augments this role
Entry · $47,550 Top of range · $134,350 (Colorado) Middle $73,010

Wages — U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Conservation Scientists). Top of the range is the highest state-level figure among states with at least 500 people in the job. AI-impact rating is PayCrunch's editorial assessment. Updated September 2026.

🆕 New & Trending AI Tools for Conservation ScientistReviewed September 2026

We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for Conservation Scientist work right now.

Julius AINEWFree / $20 mo

AI data analyst that runs statistics and charts from plain-language prompts.

How a Conservation Scientist uses it: analyze datasets and generate figures without writing code

NotebookLMNEWFree / $7.99 mo

Google tool that answers questions grounded only in the documents you give it — with citations.

How a Conservation Scientist uses it: load your own manuals, policies, or PDFs and ask questions that stay accurate to the source

ElicitFree / $12 mo

AI research assistant that finds and summarizes papers.

How a Conservation Scientist uses it: run a literature review and extract findings across dozens of papers fast

ConsensusFree / $9 mo

AI search that answers questions from peer-reviewed research.

How a Conservation Scientist uses it: get evidence-backed answers with the studies behind them

SciSpaceFree / paid

AI that explains papers and helps with literature review.

How a Conservation Scientist uses it: decode dense papers and trace citations quickly

SciteFree / $20 mo

Shows whether other studies support or contradict a paper's claims (Smart Citations).

How a Conservation Scientist uses it: check if a finding is actually backed by the wider literature before you cite it

ChatGPTFree / $20 mo

The most-used AI assistant — writing, analysis, research, and images from a plain-language chat.

How a Conservation Scientist 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 Conservation Scientist uses it: analyze big reports or spreadsheets and turn messy notes into clean, finished writing

Google GeminiFree / $20 mo

Google's AI assistant, built into Gmail, Docs, and Search.

How a Conservation Scientist uses it: draft and reply inside Google Workspace and research without leaving the page

The soil pit was open on the slope, and the landowner wanted to know what could be planted before the fall rains. The conservation scientist knelt, named the layers, and talked through drainage, compaction, and which trees would fail on that aspect even if the catalog said they were popular. Back at the truck she sketched a management note: where to keep cover, where a trail would erode, and which agency program might help with the cost of the work. Nobody was cited. The product was advice the landowner could use, grounded in the forest and the soil in front of them.

Advice on land, forest, and soil

Conservation scientists help people and agencies decide how to use and protect land. One week you might inventory a woodlot: species, size, health, and the regeneration already coming up in the understory. Another week you might read soils, map erosion, or lay out a practice that keeps sediment out of a stream. You write management plans, comments on proposed projects, and recommendations a landowner, a tribe, a city, or a company can actually carry out. The tools are a field notebook, maps and aerial imagery, a soil probe, a diameter tape or a cruising tool where timber is the subject, and a geographic information system back at the office. The places are public forests, private ranches, conservation districts, consulting firms, land trusts, and utility or watershed programs.

The people you deal with are landowners who have goals and budgets, foresters and soil specialists on your own team, biologists who care about habitat, engineers who will build the road or the culvert, and program staff who administer cost-share or permits. Your decision is what the land can support and what you are willing to sign. A plan that ignores the owner’s purpose will sit in a drawer. A plan that ignores the soil and the water will fail in the first hard storm. You learn to say both: here is what the site will do, and here is the option that meets the owner halfway.

The work splits by setting and still shares a craft. A consulting conservation scientist may spend much of the week on private land and the rest writing. A public-agency scientist may review proposals, inspect practices after installation, and advise colleagues who run a grant program. A land-trust or watershed role may mix field assessment with neighbors’ meetings. Soil-leaning jobs dwell on classification, productivity, and erosion. Forest-leaning jobs dwell on stand structure, harvest timing, and reforestation. Many postings want both, because a recommendation about a stream buffer is a soil story and a vegetation story at once.

Field time is the evidence, not a scenic extra. You walk the property line, you notice a skid trail that is already a gully, you photograph what you saw, and you write so someone who was not there can see why you ruled a practice in or out. Office time is where the map, the measurements, and the narrative become a plan with priorities. Employers trust the scientist who can do both and who will change the recommendation when the pit or the stand contradicts the first impression. A useful plan also names the sequence. The lane gets water off it before anyone replants the slope. The invasive shrubs come out before the seedlings go in. The landowner sees which year is maintenance and which year is the expensive intervention. Advice that is only a plant list, with no order and no reason tied to the soil, is a brochure. The scientist’s job is the order, the reason, and a recommendation modest enough to survive the weather.

A degree, and registration that varies by state

What the posting usually names

A degree in forestry, conservation, soil science, or a closely related field is the usual preparation. Some roles that offer forestry advice to the public also want registration as a forester. That requirement varies by state. The state board, where one exists, is the body that grants it.

Bachelor’s programs in forestry, natural resource management, environmental science, range, or soil science are the common entry. A master’s degree helps for research-heavy or senior advisory seats and for some federal specialist jobs. Employers look at fieldwork you have already done: a summer crew, a senior project with a real stand or a real soil map, a conservation-district internship. Supervised practice means a technician season or a junior planner role where a registered forester or a senior scientist reviews what you sign. Coursework that stays indoors, with no mud on it, leaves a gap the interview will find.

Forester registration is the piece that changes when you cross a state line. In some states, offering forestry services to the public requires a licence or registration from that state’s board, often after a forestry degree and a period of acceptable practice. In other states, the same advice can be given under a job title with no separate registration. Read the posting and the state’s rule before you assume a credential travels. Where a board exists, it is the grantor, and the credential proves you met that state’s education and practice requirements for forestry. Soil science roles may look for a different professional credential, or for none beyond the degree. Accreditation of a university forestry program by the Society of American Foresters, and that society’s certified-forester credential, are signals some employers recognize. Use them as additional proof of study. Follow the state rule when the state requires registration to practice.

Build a portfolio the land can verify. A management plan with the owner’s private details removed, a soil map you made, a note on an erosion practice you laid out, or a stand table you can explain is the right evidence. Be ready to say what you measured, what you inferred, and what you would refuse to promise. Conservation advice that sounds like a slogan fails the moment someone asks about slope and species.

Agencies, firms, and land trusts

Federal and state land agencies, conservation districts, universities and extension offices, environmental consulting firms, timber and land companies, utilities, and nonprofit land trusts all hire. The application should name a landscape and a product. A sentence about caring for the environment is too wide. A sentence about inventorying mixed hardwoods and writing a fix for an eroding farm lane is hireable. Match the posting. A soil conservation seat wants the pit, the practice, and a story about a landowner who installed it. A forestry seat wants stands, silviculture, and, where the state requires it, progress toward registration.

Ask who signs the plan and who visits the site after the practice is in the ground. A junior role with review from a senior scientist will teach you. A role that sends you out alone to promise results the company cannot support will burn the reputation you are trying to build. Ask whether the job is mostly private consulting, public program delivery, or review of other people’s proposals. Those calendars feel different, and the pay conversation should match the calendar. Consulting may include billable targets and travel between counties. A district job may include a steady set of cooperators and a local board. Name which one you are accepting.

References should be a crew lead, a professor who stood in the field with you, or a landowner’s agent who used your plan. Ask them to describe a recommendation you changed after you saw the site, not only your enthusiasm. In the interview, draw the property. If you cannot sketch why the road should move, you are reciting. Hiring managers in this field have walked too many failed practices to be impressed by vocabulary alone.

This advisory career sits apart from sworn fish and game enforcement. A conservation officer carries a commission, completes peace-officer or warden training, and enforces wildlife law. The scientist in this essay advises on land, forest, or soil and is hired for the plan, the inventory, and the practice. People do move between the cultures of a wildlife agency, and the jobs remain different hires with different proof. Apply for the one whose daily product you want to own.

From field technician to the plan you sign

Many scientists start as technicians or seasonal crew: measuring plots, digging pits under direction, entering data, and learning why a protocol exists. That season is worth more if you understand the decision the data will feed. Ask to see the finished plan, not only your own plot sheet. The next step is a junior scientist or forester who drafts recommendations a senior person edits. Promotion follows plans that were installed and that held up, plus the registration path if your state and your clients require it.

Later seats include senior scientist, consulting principal, district or program manager, and specialist roles in watersheds, wildfire resilience, or urban forestry. Some people move into extension and spend more time teaching landowners than writing a single property’s plan. Some move into agency leadership, where the work is program design and supervision. A few return to graduate school and shift toward research. The field skill should not disappear in any of those moves. Teams trust managers who can still read a pit and a stand.

Keep a list of properties and practices with confidential names removed: the site problem, your role, what was recommended, and what you know about the result a season later. That list is the promotion packet. It also stops you from claiming a specialty you only visited once. Depth in one landscape, plus enough range to work with both soil and vegetation, is a stronger story than a scatter of one-day site visits you cannot reconstruct.

Lay the offer against conservation scientists

Lay a conservation scientist offer against the conservation scientists series in the Occupational Employment and Wage Statistics for May 2025, and treat those dollars as pay for this advising work. The May 2025 employment figure for the series is 25,950, a headcount rather than a salary. Entry on the chart is $47,550. The national median is $73,010. The high end of the published range in Colorado is $134,350. The gap from entry to the median is $25,460. The gap from the median to that Colorado high end is $61,340.

State medians are typical pay, separate from the high end of the range. Colorado’s median is $84,820, the highest on the chart, and it sits $11,810 above the national median. Oregon’s median is $80,790, California’s is $79,810, Wisconsin’s is $79,540, and Massachusetts’s is $78,740. Florida’s median, $51,130, is the lowest charted here. Colorado’s typical pay of $84,820 and Colorado’s high end of $134,350 describe different slices of the same state’s published figures. If the job is in Colorado, Oregon, California, Wisconsin, or Massachusetts, put that state’s median next to $73,010. If the job is in Florida, the lower median is the honest local anchor, and a candidate should know that before treating the national median as the local norm.

A technician or a new graduate near $47,550 can be a fair start when a senior scientist is reviewing the work and the posting is honest about field seasons. Once you draft plans others sign, or you carry a set of cooperators on your own, the $25,460 step toward $73,010 is the gap to discuss, with a property you can describe. Registration, where your state uses it, belongs in that conversation because it changes what you are allowed to offer the public. The Colorado high end is the top of the published range, a figure to keep in mind for scarce senior responsibility in a high-paying state, and a poor demand for a first crew season. Ask whether the salary is base pay for the county you will actually drive, and whether a government grade or a consulting bonus is being folded into the same number.

Take the role when the landscape you will advise and the base pay on the letter both make sense for that state, and when you can already picture the first property you will walk.

The top of Conservation Scientist pay — and how to get there with AI

$134,350what Conservation Scientist pay reaches in Colorado

Highest state-level top-of-range annual wage for Conservation Scientists, among states with at least 500 people in the job. U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025.

And the role it leads to — Managers, All Other — reaches $311,260 in Rhode Island.

$47,550entry$73,010middle$134,350top end

Talks, displays and visitor services are treated as spending at most sites; the conservation scientist paid at the top of this range is the one whose programs pull in grant money, sponsorship and paid attendance.

Preparing illustrated lectures and interpretive talks, researching the natural history behind them, writing brochures and newspaper articles, planning public events, directing seasonal staff — this work is judged on quality and almost never on income. People who reach the top of the range attach a funding story to the identical programs: which grant paid for it, how many came, what a sponsor received in return. Drafting is where an assistant genuinely saves hours, whether that is a talk outline, a brochure or a grant narrative, but the natural history, the figures and the regulations have to be checked against sources by you before anything is printed or spoken.

Your playbook, by where you are now

Just startingMake the programs countable

  1. Record attendance, weather and audience type for every interpretive talk and guided walk you deliver, including the ones that went badly.
  2. Take photographs deliberately and caption them as you go; the images you shoot for displays are also what a funder asks for later.
  3. Write one article for a local newspaper each season and keep the clipping in the same folder as the program record.
  4. Let a model turn your research notes into a first outline for a talk or brochure, then rewrite the natural history yourself before it goes anywhere near a visitor.

What proves it: A season of program records carrying attendance, photographs and published writing.

Realistic span: your first two seasons

A few years inAttach money to what you already deliver

  1. Write one small grant application for a program you were going to run anyway, and build the budget in Microsoft Excel with staff time costed honestly.
  2. Ask a local business or a friends group to sponsor a single public event, then give them a written report afterwards whether or not they ask.
  3. Learn ESRI ArcGIS software to the point where you can map visitor pressure against habitat condition, because that map is what convinces a funder.
  4. Keep brochures and displays to a standard a sponsor will put its name on, using Adobe Photoshop and Adobe Acrobat rather than whatever is on the office machine.
  5. Take over the seasonal staff schedule, since whoever plans the staffing controls the cost side of every program.

What proves it: A funded program with your name on both the application and the closeout report.

Realistic span: years three through six

ExperiencedRun the funded side of the site

  1. Keep a rolling calendar of grant deadlines and partner renewals and treat it as part of the job rather than an extra.
  2. Set the pricing and the permit conditions for events at the site, and defend those figures to your own management.
  3. Move the record into Microsoft Access so attendance, cost and funding for every program sit together across years.
  4. Train seasonal staff from written program plans, so a funded program survives a week when you are not there.
  5. Take the management step deliberately; the people who end up running these sites are chosen from whoever already handles the money.

What proves it: A multi-year funding history tied to programs you designed, staffed and reported on.

Realistic span: seven years and up

The next 90 days

Choose the single program you deliver most often — the interpretive talk, the guided walk, the school visit — and cost it out over the next ninety days. Count your preparation hours, the seasonal staff time, the printing of brochures, the maintenance on whatever structure it happens in. Then count what it produces: attendance by date, where people travelled from, what they asked about. Put both halves on one page and take it to whoever controls the budget with a specific request attached, either a small grant you will write or a sponsor you will approach. The point is not the money in that first request. The point is that from then on your programs arrive with numbers, and the person whose programs arrive with numbers is the one asked to plan the season.

Wage figures: BLS OEWS, May 2025. The playbook is PayCrunch editorial guidance, not a guarantee of pay or placement.

Careers related to Conservation Scientist

Similar pay, same field

Where this can lead

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).

Open Google Earth Engine — it's the single highest-leverage tool in modern conservation science. It gives you free access to the entire Landsat and Sentinel satellite archive plus the compute to analyze it, so you can map land cover, detect change, and estimate vegetation and water across huge areas from your laptop. Learn it by driving it with an AI coding assistant (ChatGPT or Claude) that writes and explains the JavaScript or Python for you.

For everyday analysis and writing, pair R or Python (with Claude/ChatGPT as coding partner) with QGIS or ArcGIS for mapping, and use Elicit or Perplexity for literature and regulation lookups. All free or low-cost. These convert field and satellite data into the reports, plans, and grant-winning analyses that advance a conservation career.

The one rule, forever: Conservation data feeds legal and financial decisions — carbon credits, permits, compliance reports — so a fabricated or unverified number carries real liability. Never let a model's land-cover class, biomass estimate, or carbon figure stand without ground-truthing and an honest accuracy assessment; satellite classifications are wrong in predictable ways (cloud, shadow, mixed pixels), and you are accountable for the numbers. Strip sensitive data — precise locations of endangered species or sacred/tribal sites, and private landowner details — before it enters any cloud tool, and honor data-sovereignty agreements.
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
Map land cover and change from satellites with Earth Engine
Why this pays: Landscape-scale monitoring — deforestation, restoration progress, wildfire recovery — is exactly what agencies, NGOs, and carbon/ESG clients need and pay for. Doing it yourself in Earth Engine, instead of contracting it out, makes you the person who delivers the core product.
Google Earth EngineQGISChatGPT
1
Use Google Earth Engine to pull Sentinel-2/Landsat imagery for your area and compute indices (NDVI, NBR for burn severity) and change over time, with ChatGPT or Claude writing and explaining the code.
2
Build a defensible classification and, critically, assess its accuracy.
Copy-paste this prompt
Write Google Earth Engine (JavaScript) code to classify land cover in [my study area] from Sentinel-2 into [forest, grassland, water, bare, developed] using a random forest, with cloud masking. Then show me how to build training points, run an independent accuracy assessment with a confusion matrix and overall/producer/user accuracy, and interpret the results. Explain each step and the assumptions that could bias the classification.
A pretty map is worthless without an accuracy assessment and ground-truth. Always report confusion-matrix accuracy and verify a sample in the field before anyone acts on the map.
3
Export clean maps and figures into QGIS for the final report, with metadata documenting your imagery dates, methods, and accuracy.
What you'll haveLandscape-scale monitoring products delivered in-house — the core deliverable behind grants and consulting contracts.
2
Break into carbon and biomass monitoring
Why this pays: Carbon markets, reforestation verification, and ESG monitoring are the fastest-growing, best-paying corner of conservation. Satellite-plus-field biomass estimation is the technical service these buyers need, and it pays well above traditional agency scales.
Google Earth EngineRClaude
1
Combine satellite indices and, where available, spaceborne lidar (GEDI) in Earth Engine with field plot data to estimate above-ground biomass and carbon, modeling the relationship in R.
2
Understand the standard and its verification rules before you build the estimate.
Copy-paste this prompt
I'm supporting a [forest carbon] project under [a voluntary carbon standard like Verra VCS]. Explain, at a working level, how above-ground biomass and carbon stocks are estimated and verified: the role of field plots versus remote sensing, allometric equations, how uncertainty must be quantified and reported, and the common ways carbon estimates are challenged or fail verification. Point me to the methodology documents I must read.
Carbon numbers are audited and legally consequential. Follow the actual standard's methodology, quantify uncertainty honestly, and never let an AI estimate substitute for required field measurement and verification.
3
Package a repeatable monitoring-and-verification workflow you can offer as a service or bring to an employer as a specialty.
What you'll haveA high-demand carbon/ESG monitoring specialty — the lane where conservation pay reaches and exceeds the top of the range.
3
Model species and habitat to guide management
Why this pays: Species distribution and habitat-suitability models drive land-use decisions, mitigation, and restoration siting — the analyses that make you indispensable on planning teams and win competitive grants. AI coding assistance makes rigorous modeling accessible without a full quant background.
RMaxEntClaude
1
Build species distribution models in R (or MaxEnt) using occurrence data and environmental layers, with Claude writing and explaining the workflow so you can defend every choice.
2
Get the modeling design right, where most SDMs go wrong.
Copy-paste this prompt
I'm building a species distribution model for [a species of concern] in R using occurrence records and environmental predictors. Walk me through a defensible workflow: handling sampling bias and pseudo-absences, checking predictor collinearity, choosing an algorithm, spatial cross-validation (not random), and honest evaluation metrics. Explain each pitfall that produces an over-optimistic model, and how I'd communicate uncertainty to a land manager.
SDMs are easy to build and easy to get wrong. Use spatial cross-validation, watch for sampling bias, and present uncertainty — managers make real decisions on these outputs.
What you'll haveDecision-grade habitat models that guide management — the analytical value that earns senior roles and funding.
4
Compress reports, NEPA documents, and grant writing
Why this pays: Conservation runs on documents — management plans, environmental assessments, grant proposals. AI that drafts structure and synthesizes regulation and literature lets you produce more, higher-quality documents, the output that drives promotions and successful funding.
ClaudePerplexityElicit
1
Use Claude to draft the structure and boilerplate of a management plan or environmental assessment, and Perplexity to pull current, citable regulatory requirements.
2
Turn scattered findings and rules into a defensible document skeleton.
Copy-paste this prompt
Act as an environmental planning assistant. Draft the section outline and a professional template for a [forest management plan / NEPA environmental assessment] for [a specific project type]. Cover purpose and need, affected environment, alternatives, impacts (soil, water, wildlife, fire), mitigation, and monitoring. Note which sections require primary field data and which require specific regulatory citations. Do not fabricate any site findings or regulations.
AI drafts structure and language, never conclusions or citations. Verify every regulatory reference and base every finding on your own verified data — these documents carry legal weight.
3
Use Elicit to build the literature and evidence base for the science sections, checking every source against the real paper.
What you'll haveMore and better plans, assessments, and proposals produced faster — the output that drives advancement and funding.
5
Automate field data into decision-ready dashboards
Why this pays: Turning raw monitoring data into clear, current dashboards for landowners, agencies, and funders is what makes your work visible and rehireable. AI-assisted data pipelines let you deliver living, professional reporting without a data team.
R (Shiny)ArcGIS OnlineChatGPT
1
Pipe field and remote-sensing data into a simple dashboard — an R Shiny app or an ArcGIS Online dashboard — so stakeholders see monitoring results update instead of waiting for a PDF.
2
Have AI scaffold the reproducible pipeline you maintain.
Copy-paste this prompt
I collect [vegetation transect and water-quality] data each season and want a reproducible workflow that cleans it, computes standard indicators and trends, and outputs a simple dashboard for non-technical stakeholders. Suggest a practical R-based pipeline (data cleaning, QA checks, trend calculation, Shiny dashboard), explain each step, and list the data-quality checks that catch common field-entry errors.
Automation is only as good as the QA. Build in data-quality checks and spot-verify outputs; a clean dashboard built on bad field data misleads decision-makers.
What you'll haveLiving, decision-ready reporting that keeps you visible and rehired — the reputation behind steady, senior-level work.
Your 12-month sequence to the top of the range

How the plays above stack into a path from median pay toward the $134,350 tier.

Month 1
Learn Google Earth Engine basics with an AI coding assistant: pull imagery, compute NDVI/NBR, and map change for one real area with an accuracy check.
Months 2-3
Add R/Python analysis and QGIS mapping to your workflow, and use AI to draft a report or grant section you'd otherwise have delayed.
Months 3-6
Go deep on one high-value specialty — carbon/biomass monitoring or species distribution modeling — and build a repeatable, defensible workflow.
Months 6-12
Package your monitoring products into dashboards and target the higher-paying lanes: carbon markets, ESG verification, or senior agency/NGO roles.
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.

McKinney Python for Data Analysis, 3rd

Same live O’Reilly 3rd already on data-scientist / python-developer / market-research-analyst / botanist. This leftover page says pair R or Python (with Claude/ChatGPT as coding partner) and Months 2–3 is Add R/Python analysis and QGIS mapping to your workflow. Not CompTIA Data+ and not leftover Ross Exam P (that is actuary). Confirm 109810403X. Live page HTTP 200, no PC_GEAR / amazon.com/dp / tag=paycrunch-20 at 2026-09-17 3:31 PM PT.

Next steps for a Conservation Scientist

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.

Conservation Scientist work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Conservation Scientists (SOC 19-1031). 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 Biology, which is what the course searches below actually query.

Conservation Scientists in this dataset list Autodesk AutoCAD among the tools in use, so a program that names that stack is a better fit than a survey course.

Biology programs on Coursera for Conservation Scientist work

Coursera search for biology — a professional certificate or bachelor's-level coursework that lines up with science, not a generic professional-development aisle.

Biology courses on edX

edX search for biology, aimed at science (SOC 19-1031). Same field as the Coursera link, different university catalog.

Screened remote and flexible Conservation Scientist listings on FlexJobs

FlexJobs screens remote, hybrid, freelance, and flexible listings so you are not wading through unverified ads. This is a job-board search for Conservation Scientist work, not a claim that they list a counted SOC 19-1031 inventory.

Build a Conservation Scientist resume on Resume Now

Write a Conservation Scientist resume, or one aimed at Managers, All Other, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.

Build a Conservation Scientist resume on Zety

A Conservation Scientist resume that names the actual tasks on this page, or the step-up title Managers, All Other, beats a blank template when you apply.

What Conservation Scientists earn by state

These are the Bureau of Labor Statistics’ own figures for Conservation Scientists, state by state — not a cost-of-living adjustment applied to the national number. Only states employing at least 500 people in the occupation are shown, because a state median drawn from a handful of workers is noise rather than a signal.

Colorado
$84,820
highest of them · +16% vs the national median
Florida
$51,130
lowest of the 19 states that qualify · -30% vs the national median
The same job pays $33,690 more a year at the median in Colorado than in Florida — 66% higher. That gap is what the Bureau measured, before any question of what it costs to live in either place. Colorado also carries the top of this job’s range, $134,350 — the figure quoted at the head of this page.
Colorado$84,820Oregon$80,790California$79,810Wisconsin$79,540Massachusetts$78,740Washington$78,450New York$76,990Montana$73,920

Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025, SOC 19-1031. 19 states clear the 500-employee reporting floor for this occupation; those below it are left out rather than shown with a wide error band.

Free data. Use any of it.

PayCrunch publishes verified, BLS-sourced salary + AI-playbook data on 1,000+ professions — free, no signup.

Frequently asked
Will AI replace conservation scientists?
No. AI can classify satellite imagery and draft documents, but it can't ground-truth a plot, walk a burn, negotiate with a landowner, judge an ecosystem's condition, or take professional responsibility for a management plan or carbon estimate. The work is field-based and accountable. AI is augmentation: scientists who use it monitor larger areas and produce more defensible analyses, which is what funders and employers reward.
Can I trust an AI land-cover map or carbon estimate?
Only after you validate it. Satellite classifications fail in predictable ways — clouds, shadows, mixed pixels — and AI-written models can be subtly wrong. Always run an accuracy assessment, ground-truth a sample, quantify uncertainty, and follow the actual methodology when numbers feed carbon credits or compliance. These figures carry legal and financial weight, and the accountability is yours.
How does AI actually raise a conservation scientist's pay?
By making you the person who delivers landscape-scale products in-house and by opening higher-paying lanes. Earth Engine remote sensing, biomass/carbon monitoring, and species modeling are exactly what carbon markets, ESG, and compliance clients pay for — well above traditional agency scales — and AI makes those technical analyses accessible without a dedicated data team.
Is it safe to put field or landowner data into these tools?
Strip the sensitive parts first. Precise locations of endangered species or sacred/tribal sites and private landowner details shouldn't go into cloud tools that train on inputs. Generalize or remove them, honor data-sovereignty and confidentiality agreements, and keep regulated project data inside approved workflows.
Which skill should I build first?
Google Earth Engine, driven with an AI coding assistant. It's free, it scales your analysis from a plot to a landscape, and it underlies the highest-value services in the field — change detection, biomass, and monitoring. Add R/Python and QGIS next, then specialize in carbon or species modeling.
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.

Sources