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PayCrunch AI Playbook · Science

How a biologist reaches the top of the range

$211,910top of the range in District of Columbia · middle $98,920 / yr
AI augments this role

Biologists in the United States earn a median of $98,920 a year. Pay starts near $60,430. Pay reaches $211,910 at the top of the range in Washington D.C., the best-paying location 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 (Biological Scientists, All Other, SOC 19-1029). Last checked 9 September 2026.

Entry level
$60,430
Top of the range · District of Columbia
$211,910
Education
Bachelor's or Master's degree in Biology
Lower disruption Higher exposure AI augments this role
Entry · $60,430 Top of range · $211,910 (District of Columbia) Middle $98,920

Wages — U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Biological Scientists, All Other). 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 BiologistReviewed September 2026

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

Julius AINEWFree / $20 mo

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

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

SciSpaceFree / paid

AI that explains papers and helps with literature review.

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

Knee-deep in a marsh, a biologist finishes a plant count along a line they laid at dawn, then drives back to a bench that still holds yesterday's samples. The morning was mud, a notebook, and a decision about whether a plot had been trampled by something other than the study. The afternoon is labels, a microscope, and a call to a land manager who needs to know what the count can support. Field clothes and a lab coat can belong to the same week. The occupation is that range of living systems, studied closely enough that someone else can use the result.

A transect at dawn and a bench after lunch

Biologists study living things in the field, in the lab, or in both. One person may track populations, identify organisms, and write what a site is doing over a season. Another may design a controlled experiment on cells, tissues, or whole organisms and spend the week at a bench. The Bureau title behind this page is deliberately broad, so the day is not a single species and not a single room. What repeats is observation you can defend: a method, a record, a comparison, and a sentence about what the living system actually did.

Field days mean weather, access, and logistics. You lay plots or transects, collect specimens or measurements, and keep the notes tight enough that a crew member could repeat the visit. You deal with landowners, agency staff, boat or vehicle operators, and technicians who need the plan before they leave the truck. The decisions are practical and scientific at once. Is this site still comparable to last year. Is the organism in hand the one you think it is. Do you stop collecting because the permit's conditions, or the animal's condition, say stop. Tools are maps, sampling gear, identification references, and a notebook that survives getting wet.

Lab days mean cultures, dissections, microscopy, growth rooms, and experiments with controls a skeptic would accept. You might work in a university department, a natural-resource agency, an environmental firm, a museum, a biotech group that still wants an organismal scientist, or a field station with a small bench in the back. People around you include technicians, graduate students, a senior scientist, and the outside user of the work: a regulator, a restoration crew, a company, or a journal editor. The decision that matters is what you will claim. A count, a growth curve, or a community list that overreaches the design will be used by someone who never saw the marsh.

Keep this seat distinct from its neighbors. Biochemistry, on its own page, is the chemistry of the molecules of life. Bioinformatics is computation on biological files, judged by whether a biologist can trust the analysis. Biomedical research aims at illness and at pushing a result toward health. A biologist may collaborate with all three. The job you are reading about here is the study of organisms and living systems, outdoors or indoors, under a broad life-science title. Say which habitat or which experimental system you know. A hiring scientist cannot place "I love life" on a crew schedule.

A wide life-science bucket, and the wages tied to it

The pay figures belong to the Bureau of Labor Statistics grouping Biological Scientists, All Other. The code is SOC 19-1029. The release is Occupational Employment and Wage Statistics for May 2025. "All Other" means the series holds biological scientists who fall outside the Bureau's narrower life-science titles, which is why a field ecologist and a lab biologist can both land here. Use the series for that kind of biological work. It is a poor quote for a pure programming job or for a clinical profession with its own licence and its own chart. No employment headcount is printed for the series, so leave headcount out of the conversation and stay with the wages.

The degree employers read first

Study, then the work itself

A degree is the usual door. No general licence covers biologists. Employers look next at studies you have finished: a crew you can describe, an experiment with controls, and writing someone outside the lab could use.

A bachelor's in biology or a close field is the common start for technician work and for some field jobs. A master's often marks the person who can run a study with less daily direction, write the report, and train newer hands. Doctoral training is what employers usually expect when the role is an independent research program, a university scientist's chair, or a senior agency post that sets the science rather than carrying it out. Postings differ. Some environmental firms and agencies hire strong bachelor's and master's biologists into work that is serious and permanent. Read the degree line. If the line says doctorate, a field season alone will not substitute. If the line says bachelor's plus experience, a finished study matters more than another year of coursework you were not asked to take.

Preparation is the degree, supervised field or lab time, and a record of what you did. Supervised practice may be a technician post, a thesis under a professor, or a seasonal crew led by a biologist who signs the protocol. Your portfolio can be a report with site names generalized, a poster, a thesis chapter, or a methods page you can talk through. Be ready to describe a day that went wrong: a plot you had to drop, a culture that contaminated, an identification you corrected. That story shows judgment. A list of organisms you enjoy does not. Employer training will add the local safety rules, the local data templates, and the permissions required on a given refuge, forest, or campus. Those permissions are site access. They are a different thing from a general professional licence, which this occupation does not use as its gate.

Specialist certificates exist in corners of biology, from fieldwork skills to particular taxonomic groups, granted by the societies or schools that run them. Treat them as optional fluency. Lead with the degree and with a study. If a posting is silent about extra cards, do not delay an application to collect them. If a posting names one, learn what body grants it and what work it is meant to show, and keep exam trivia out of your story. The biologist across the table wants to know whether you can be left with the data.

Joining a crew or a research group

Universities, federal and state natural-resource offices, environmental and ecological consultancies, museums, field stations, and companies with a biological research arm all hire. Apply to the habitat or the experimental system you have already touched, and name one adjacent skill you are building. A person who has done one honest field season is easier to schedule than a person who has only taken the lecture. A person who has kept a lab experiment alive is easier to trust with a bench than a person who liked the idea of research. Seasonal crews are a real door. Treat them as professional work: show up, keep the notes, and leave a record the lead can cite.

Ask who designs the study and who will read your notes. A technician seat under a biologist who still goes to the field is how people learn the craft. A seat that is only labor for a project nobody is scientifically responsible for teaches endurance and little judgment. For a biologist title, ask what you would be expected to deliver in the first year: a monitoring report, a paper, a permit-ready dataset, an internal finding. For consulting, ask how much of the week is science and how much is client schedule. Client work can be excellent biology. It should be described honestly so you compare pay with the right kind of pressure.

Ask for referees who watched your notes survive a bad day in the mud or at the bench. A crew lead, a professor, or a senior biologist who can describe an identification you corrected, or a mistake you reported instead of hiding, will help you. Bring a simple map or a simple experimental sketch to interviews that invite it. Drawing the comparison is more persuasive than adjectives. If you are changing from a neighboring science, say what you already do and what a first season would have to teach you. Groups that work on living systems have little patience for bluffing about a species or a method. Candor is part of the hire.

Technician, biologist, senior scientist

The path to follow is technician, then biologist, then senior scientist. A technician carries methods, keeps samples and plots in order, and produces measurements someone else designed. A biologist designs or co-designs the work, interprets it, and signs the conclusion. A senior scientist sets a program, mentors the group, deals with funders or agency leadership, and is accountable for the science others carry out. Consulting firms and agencies use different badges for the same climb. Watch whether you are executing a protocol or deciding what the protocol should be next season.

Promotion follows studies that finished and held up. A technician who can write the methods paragraph and notice when a site is no longer comparable is the one biologists trust with more design. A biologist who can fund or justify the next season, and who still knows the organisms in person, is the one considered for the senior role. Keep a list of projects, your role, the system you studied, and the decision the result changed. That list is your case for a title change. If the list is only tasks performed, you remain in the technician story until the design responsibility is real. Pay should match that story. A senior title without senior decisions is a weak reason to reach for the top of the range.

Placing an offer against the published range

Early pay on this page begins near $60,430. The national median, the typical middle for the series, is $98,920. The gap between those two points is $38,490. At the top of the District of Columbia range, the page shows $211,910, for places with enough people in the occupation for the Bureau to publish it. The page's lead also names that location as Washington, D.C. Climbing from the country's middle to that District top covers $112,990. Maryland shows a median of $121,680, and Maryland's median runs $22,760 above the country's middle. That Maryland figure is typical pay in the state. It is a different figure from the District's high end. California's median reads $113,530. Washington's median reads $108,110. Massachusetts shows $107,100. New Jersey shows $104,750. Name a median when you mean typical pay. Name $211,910 when you mean the high end in the District of Columbia.

A technician offer should be read against $60,430. The $38,490 up toward $98,920 becomes the right topic when you already run methods, train seasonal staff, or draft the interpretation, and the letter still pays you like extra hands on someone else's study. A biologist who owns a study can anchor on $98,920. If that job is in Maryland and you mean typical pay there, bring in the $22,760 that sits between the national median and Maryland's $121,680. The long $112,990 from the national median to $211,910 fits a senior scientist, a scarce specialty, or a program lead, especially where the District of Columbia high end is the relevant top of the range. It is the wrong anchor for a seasonal technician or a new bachelor's hire. California, Washington, Massachusetts, and New Jersey each offer a median you can cite as typical pay in that state, without treating any of them as the high end.

Say the rung, then the dollar. For a technician, ask what finished responsibility would justify crossing the $38,490: independent plots or assays, a report in your voice, supervision of a crew. For a biologist, begin at $98,920 and add a state median only for the state where the work actually sits, choosing among Maryland, California, Washington, Massachusetts, and New Jersey. For a senior scientist arguing the District high end, walk the $112,990 and ask which scope the employer means: one study, a program, a region, a group you would hire. Do not add a headcount. This page's wage facts are the entry, the median, the District high end, five listed state medians together with the three gaps printed beside them. That set is enough for a serious talk.

When you take the job, keep the field notes and the lab notes as careful as the negotiation. You are building a path from technician to biologist to senior scientist. The degree is the door. A general licence is outside the occupation, so the studies you can explain are the proof employers use. Set the offer beside $60,430 if you are still carrying someone else's design, beside $98,920 if the study is yours, and beside either Maryland's $121,680 or the District's $211,910 only after you know whether you mean typical pay or the high end of the range.

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

$211,910what Biologist pay reaches in District of Columbia

Highest state-level top-of-range annual wage for Biological Scientists, All Other, 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 — Data Scientists — reaches $224,920 in California.

$60,430entry$98,920middle$211,910top end

Two biologists can do identical gene expression work; the one paid at the top of the range is the one whose results left the lab as a citable publication and a queryable dataset, rather than a slide in an internal meeting.

Measuring gene expression, determining gene function, and pulling from public and proprietary genomic and proteomic databases generate a great deal of result and very little visible record, and careers stall exactly there. What gets rewarded is communication and curation: project reports somebody reads, conference presentations somebody remembers, and a data model that makes last year's experiment answerable this year. Drafting help and figure automation shorten both jobs, but only when the underlying records were kept in a shape worth publishing in the first place.

Your playbook, by where you are now

Just startingKeep records worth publishing

  1. Decide the sample and file naming scheme before the experiment rather than afterwards, and never break it.
  2. Store results in a Microsoft SQL Server table with metadata attached, instead of a folder of spreadsheets named by date.
  3. Read one paper a week outside your immediate subject and note the instrumentation or biochemistry behind it, because that habit is half of keeping current.
  4. Redraw your own figures in Adobe Illustrator until they stay legible at conference-poster size.

What proves it: A dataset from your first project a colleague can locate and interpret without asking you anything.

Realistic span: the first two years

A few years inGet your name on the output

  1. Take first authorship on something small and finish it, rather than second authorship on something ambitious that never lands.
  2. Give the conference talk. Rehearse against Otter.ai and read the transcript to find the sentences that lost the room.
  3. Learn enough Bioconductor to run your expression analysis start to finish instead of describing it to whoever does.
  4. Turn the recurring project report into a template that fills from your database, so reporting stops competing with bench hours.
  5. Use Claude to argue against your interpretation before a supervisor does, then check every counterpoint against the data.

What proves it: A published first-author paper, or a conference talk you were invited back to give again.

Realistic span: years three to six

ExperiencedDecide what the lab works on

  1. Consult with researchers around you on how to frame their problems, and recommend the computational strategy rather than executing it.
  2. Direct technicians and support staff, and write the protocols that make their output comparable across people.
  3. Add a spatial layer with ESRI ArcGIS software wherever sampling location matters, and publish the map alongside the result.
  4. Move toward the biochemistry and biophysics track that pays above this one, and note District of Columbia employers pay biologists most.

What proves it: A research programme running under your direction, with staff and a budget attached.

Realistic span: seven years and up

The next 90 days

In the next ninety days, go back to a finished project nobody wrote up and finish it. Pull the raw data, reconstruct what was measured, rebuild the figures cleanly, and write it as either a paper or a project report someone outside the group could act on. Almost every biologist has two or three of these sitting unfinished, and each is a result that already cost the money and produced nothing citable. Finishing one teaches the whole chain, records through analysis through figures through argument, on work you already understand. It also gives you something concrete to point at, which is a very different conversation from listing techniques you know.

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

Careers related to Biologist

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).

Point AI at your survey backlog first. If you have camera-trap images or audio recordings, run them through MegaDetector/Wildlife Insights (images) and BirdNET (audio) — the identification labor that used to take weeks of squinting collapses into days you spend verifying, not sorting. This is the single biggest time win in field biology.

For free skill-building, use iNaturalist and Merlin Bird ID to sharpen species ID, pull open occurrence data from GBIF, and use ChatGPT or Claude to write R for your analyses. Verify every AI identification of a rare or sensitive species before it goes in a report.

The one rule, forever: AI species IDs and model outputs are hypotheses to verify, not confirmed records — a misidentification or a shaky occupancy estimate can misdirect a permit, a conservation decision, or a protected-species call you're legally accountable for. Confirm AI identifications (especially rare or sensitive taxa) with expert review, protect the locations of endangered species and sensitive sites, cite data provenance, and never present model predictions as field-verified fact.
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
Process camera-trap and bioacoustic surveys at scale
Why this pays: In research and environmental consulting, the bottleneck is turning terabytes of images and audio into verified detections. AI that pre-sorts and identifies collapses that labor by an order of magnitude — so you cover more sites, run larger surveys, and bill more projects, the throughput that carries a biologist toward senior pay.
Wildlife InsightsMegaDetector (PyTorch Wildlife)BirdNET
1
Run camera-trap images through MegaDetector or Wildlife Insights to drop the empty frames and pre-label animals, and process acoustic recorders with BirdNET for bird and (with the right models) bat or amphibian detections.
2
Use AI to design a verification and analysis workflow around the AI detections.
Copy-paste this prompt
I have [N] camera-trap nights across [M] stations processed by MegaDetector, and [X] hours of audio run through BirdNET. Design a rigorous workflow to go from AI detections to a defensible species inventory: what confidence thresholds to set, how many detections to manually verify per species (especially rare ones), how to handle false positives, and how to summarize detection/effort for a report. Note where expert verification is non-negotiable.
AI pre-labels; you confirm. Manually verify a sample of every species and 100% of rare/sensitive detections — a false ID in a report is your liability.
What you'll haveWeeks of manual sorting turned into days of verification — more sites surveyed and more projects delivered per season.
2
Model species distributions and habitat suitability
Why this pays: Where a species can live drives permitting, mitigation, and conservation planning — the high-stakes questions clients and agencies pay for. A biologist who builds credible species distribution and habitat models delivers exactly those answers, a quantitative, senior-level capability well above routine field survey work.
Wallace / MaxEntGoogle Earth EngineR
1
Build a species distribution model in Wallace (a MaxEnt-based R workflow) using occurrence data from GBIF and environmental layers, and pull remote-sensing habitat variables (land cover, NDVI, terrain) from Google Earth Engine.
2
Use AI to set up a defensible modeling and validation workflow.
Copy-paste this prompt
Help me build a species distribution model for [species] in [region]: which occurrence and environmental predictors to use and how to reduce collinearity, how to address sampling bias in the occurrence data, the model settings and how to tune them, and how to validate honestly (spatial cross-validation, AUC/omission). List the ways SDMs mislead and how to caveat the map for a permitting audience.
SDMs are only as good as the occurrence data and assumptions — validate spatially, disclose uncertainty, and never present a suitability map as confirmed presence.
What you'll haveCredible habitat and distribution models for permitting and planning — the quantitative deliverable that pays at senior rates.
3
Automate ecological statistics in R
Why this pays: Defensible conclusions rest on proper analysis — occupancy and abundance models, biodiversity indices, trend tests. Using AI to write and explain that R code means your reports withstand agency and peer scrutiny and you produce them faster, the rigor-plus-speed that distinguishes a principal biologist from a field tech.
ChatGPT (Advanced Data Analysis)Julius AIR
1
Use ChatGPT Advanced Data Analysis or Julius AI on your survey data to run the appropriate model, and have it generate documented R you can rerun and defend.
2
Get AI to write and justify the analysis so you can verify the ecology and stats.
Copy-paste this prompt
Write documented R to fit a single-season occupancy model (package unmarked) to this detection/non-detection data [describe format] with [covariates] on detection and occupancy. Report estimated occupancy and detection probability with confidence intervals, check goodness-of-fit, and plot the covariate effects. Explain each modeling assumption so I can confirm my data meet it, and flag when a different model would be more appropriate.
Confirm the model matches your survey design and that assumptions hold — a clean-looking estimate from the wrong model is worse than none. You own the analysis.
What you'll haveRigorous, reproducible, defensible analyses produced quickly — the credibility and speed behind senior and principal roles.
4
Speed field ID and biodiversity data work
Why this pays: Breadth across taxa and fast, accurate identification make you more useful on more projects — and more billable. AI ID tools and open biodiversity databases let you confirm species in the field and assemble regional context in minutes, expanding the range of surveys you can credibly lead.
iNaturalist (Seek)Merlin Bird IDGBIF
1
Use iNaturalist and Merlin for real-time ID support in the field (always confirming with diagnostic features), and pull regional species lists and occurrence context from GBIF to scope a site before you visit.
2
Use AI to build a site pre-assessment from open data.
Copy-paste this prompt
For a biological survey at [location/coordinates and habitat type], build a pre-field brief: the species of conservation concern (state/federal listed) likely present, their habitat associations and survey seasons/protocols, the invasive species to watch for, and the diagnostic features that distinguish commonly confused pairs in this region. Cite the data source, and flag which species require a permitted or specialist surveyor.
Use this to prepare, not to conclude — confirm listed-species status against official state/federal sources, and verify every field ID with diagnostic characters.
What you'll haveFaster, broader, better-prepared field surveys — the versatility that puts you on more projects and raises your billable value.
5
Accelerate permitting and technical reporting
Why this pays: Environmental consulting is a deliverable business, and biological assessments, ESA and NEPA documents, and survey reports are the product. Using AI to synthesize literature and draft these reports protects project margin and builds a reputation for thorough, defensible work — the engine of repeat clients and promotion to principal.
ElicitClaudePerplexity
1
Use Elicit to assemble the literature on a species or impact question, read the primary sources, then use Claude to draft the report structure and turn your verified findings into agency-ready prose in your firm's format.
2
Use AI to build the compliance backbone of the deliverable.
Copy-paste this prompt
Outline a [Biological Assessment for ESA Section 7 consultation] for a [project type] that may affect [listed species]. List the required sections and what each must contain, the analysis a reviewing agency (USFWS/NMFS) expects for effects determinations, the common reasons these documents get sent back, and a checklist. Cite the governing regulation/guidance so I can verify each requirement, and leave placeholders for my field data.
Verify every regulatory requirement against the actual statute/agency guidance, and never let AI fabricate species data or citations — you're accountable for the determination.
What you'll haveThorough, defensible reports and permits delivered faster — protected margins and the reputation that drives advancement.
6
Become the quantitative biodiversity-data specialist
Why this pays: The biologist who can build reproducible pipelines, run the AI models, and lead a data-rich monitoring program becomes the one clients and agencies ask for by name. That scarce blend of field credibility and data/AI skill is what commands the top of the pay band and principal roles.
R / RStudioGitHubGoogle Earth Engine
1
Turn your best analysis into a reproducible, documented R pipeline on GitHub (camera-trap-to-occupancy, or SDM-to-map), and design a monitoring program that combines AI-processed field data with remote sensing.
2
Use AI to structure a hireable, credible specialization plan.
Copy-paste this prompt
Act as a mentor for quantitative ecology. I'm a field biologist strong on natural history but light on data science. Build a 6-month plan to become the go-to biodiversity-data specialist: the R and modeling skills in order (data wrangling, occupancy/N-mixture, SDMs, spatial analysis), 3 portfolio projects using open data and AI field tools, and the concepts I must defend to reviewers and clients.
Publish only with honest uncertainty and proper data attribution — calibrated, reproducible work is what earns the reputation, not flashy maps.
What you'll haveA rare field-plus-data profile and a visible portfolio — the specialization that anchors principal-level, pay at the top of the range.
Your 12-month sequence to the top of the range

How the plays above stack into a path from median pay toward the $211,910 tier.

Month 1
Run your camera-trap/audio backlog through MegaDetector/Wildlife Insights and BirdNET, and start learning R analysis with AI. Verify every rare-species ID.
Months 2-3
Fit a real analysis (occupancy or biodiversity index) in R with AI help and build AI-assisted site pre-assessments from GBIF.
Months 3-6
Build a species distribution/habitat model and use AI to speed a technical report or biological assessment.
Months 6-12
Package a reproducible pipeline and portfolio, and position as the quantitative biodiversity-data specialist — the principal track.
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.

Bolstad, GIS Fundamentals, 7th ed.

Same live Bolstad 7th already on gis-analyst / urban-planner / forest-ranger / cartographer / hydrologist / park-ranger / archaeologist / wildlife-biologist / paleontologist / city-planner (ASIN 0971764751). This leftover page is BLS Biological Scientists, All Other (SOC 19-1029); play 2 is Model species distributions and habitat suitability; tools name Wallace / MaxEnt / Google Earth Engine / R; Months 3–6 is Build a species distribution/habitat model and use AI to speed a technical report or biological assessment; play 5 names ESA and NEPA documents. GIS fundamentals text for leftover habitat-model / geospatial / SDM work — not leftover GISP as a card. Confirm 0971764751. Live page HTTP 200, no PC_GEAR / amazon.com/dp / tag=paycrunch-20 at 2026-09-18 12:49 AM PT. Source page: forest-ranger.

Next steps for a Biologist

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.

Biologist work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Biological Scientists, All Other (SOC 19-1029). O*NET Job Zone 5 is typical: graduate or professional school, so the honest next credential is a graduate-level or professional certificate — not a random catalog dump.

The occupation's listed knowledge area is Biology, which is what the course searches below actually query.

Biologists in this dataset list Amazon Web Services AWS software 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 Biologist work

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

Biology courses on edX

edX search for biology, aimed at science (SOC 19-1029). Same field as the Coursera link, different university catalog.

Screened remote and flexible Biologist 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 Biologist work, not a claim that they list a counted SOC 19-1029 inventory.

Build a Biologist resume on Resume Now

Write a Biologist resume, or one aimed at Data Scientists, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.

Build a Biologist resume on Zety

A Biologist resume that names the actual tasks on this page, or the step-up title Data Scientists, beats a blank template when you apply.

What Biologists earn by state

These are the Bureau of Labor Statistics’ own figures for Biological Scientists, All Other, 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.

Maryland
$121,680
highest of them · +23% vs the national median
Missouri
$63,290
lowest of the 28 states and D.C. that qualify · -36% vs the national median
The same job pays $58,390 more a year at the median in Maryland than in Missouri — 92% higher. That gap is what the Bureau measured, before any question of what it costs to live in either place. The top-of-range figure quoted at the head of this page, $211,910, is a different statistic in a different place: it is the 90th-percentile wage in District of Columbia. The state that pays the typical worker most and the state where the best-paid go highest are not always the same one.
Maryland$121,680California$113,530Washington$108,110Massachusetts$107,100New Jersey$104,750New York$104,120Pennsylvania$100,780North Carolina$100,070

Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025, SOC 19-1023. 28 states and D.C. 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 biologists?
No — it removes the drudgery, not the biologist. AI can pre-sort images, name a call, or map habitat, but it can't design a defensible survey, verify a rare-species detection, judge whether a model is credible, or sign a regulatory determination. Biologists who use AI process far more data and take on bigger projects; those who don't will be out-produced by peers who cover ten times the ground.
Can I trust AI species identifications?
As a first pass, yes; as a final record, only after verification. Tools like MegaDetector, BirdNET, and iNaturalist are excellent at pre-labeling, but they make errors — especially on rare, cryptic, or regionally unusual species, which are exactly the ones that matter for permits. Verify a sample of every species and every sensitive detection with diagnostic features or expert review before it enters a report.
Do I need to learn R or coding to benefit from AI?
AI-assisted R is the highest-leverage skill you can add. It's what turns field data into the occupancy models, distribution maps, and trend analyses that agencies and clients trust — the work that separates a principal biologist from a field tech. AI writes and explains the code alongside you, so the learning curve is far shorter than it used to be.
How does AI actually increase a biologist's pay?
By multiplying your throughput and adding quantitative skills. AI-processed survey data lets you cover more sites and bill more projects; species distribution models and rigorous R analysis are senior-level deliverables; and faster, defensible reports protect consulting margin. That combination of scale and quantitative credibility is what moves you toward the $211,910 tier and principal roles.
Which AI tool should a biologist prioritize?
Start with the field-AI tool that fits your data — MegaDetector/Wildlife Insights for cameras or BirdNET for audio — because it saves the most time immediately. Then invest in AI-assisted R analysis, which is the durable skill that underpins every higher-paying quantitative and principal role.
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