What a political scientist adds after the doctorate
$195,190top of the range in District of Columbia · middle $142,080 / yr
AI augments this role
Political Scientists in the United States earn a median of $142,080 a year. Pay starts near $83,350. Pay reaches $195,190 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 (Political Scientists, SOC 19-3094). Last checked 9 September 2026.
Entry level
$83,350
Top of the range · District of Columbia
$195,190
Education
Master's or Doctoral degree
Wages — U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Political 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 Political ScientistReviewed September 2026
We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for Political Scientist work right now.
Julius AINEWFree / $20 mo
AI data analyst that runs statistics and charts from plain-language prompts.
How a Political 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 Political 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 Political 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 Political 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 Political 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 Political 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 Political 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 Political 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 Political Scientist uses it: draft and reply inside Google Workspace and research without leaving the page
A day spent on evidence
A political scientist studies how power is organized and how public decisions get made. The daily work is research. You read what other scholars and agencies have already found. You build or clean a dataset. You test an idea against that data, and you write the result so a reader can see the claim and the limit of the claim. The topic might be a legislature, a court, an agency, a voting rule, a public budget, or the way people in different countries answer similar political problems. The constant is the method: a question stated clearly, evidence you can show, and a conclusion that does not outrun the evidence.
In a research office the morning may be quiet and still demanding. You check a table that did not match yesterday's file. You reread a statute summary because a colleague flagged a line. You draft two paragraphs of a brief that a non-specialist will have to use. In a university the same skills show up as a paper, a class, and a stack of student work. In either setting, the reputation comes from being careful in public. A finding that cannot be retraced is not a finding. Colleagues remember who documents the steps and who hides the messy part.
Running a campaign is a different occupation. A political scientist may study elections, turnout, or public opinion as research subjects. That study uses surveys, administrative records, and published results. It does not hand you a field plan for a candidate, and it should not be confused with campaign work. If you want the research career, practice designing studies and writing them up. If you want campaign work, look for that hiring path on its own terms. Mixing the two in a resume confuses the people who hire researchers.
Collaboration is ordinary, and it has etiquette. A project may include a statistician, a lawyer, and a program specialist who knows the forms the public actually files. You translate among them without pretending to hold their licenses or their caseloads. Credit the person who built the file. Say when a result is sensitive to one coding choice. Government readers in particular want the limitation next to the headline, because they may be asked about it in a hearing or a budget markup. A brief that hides the weak spot creates a worse week later than a brief that leads with it.
Tools change, and the habit does not. Spreadsheets, statistical software, and archival databases are all in use. Learn the one your office relies on before you push the office to switch. Document the file names, the date of the extract, and the rule you used to drop a record. The next researcher, who may be you in eight months, has to reproduce the number. That reproducibility is the quiet center of the job, whether the final product is a journal article, a legislative brief, or an internal evaluation nobody outside the agency will see.
What the graduate degree is doing
Graduate school is the usual preparation. Universities grant the degree. A master's degree can open applied research jobs in agencies and in research organizations, especially when the program trained you in methods and in writing for non-academic readers. A doctorate is the common path into university posts and into senior research roles that expect you to lead a project. The degree proves you can frame a problem, use the methods your field trusts, and finish a substantial piece of original work. It does not, by itself, prove you can brief a deputy secretary or manage a contract. Those skills show up in the jobs you take alongside the degree or just after it.
People prepare by doing the undergraduate work seriously: political science or a close field, quantitative or historical methods, and at least one long paper a faculty member will stand behind. Applications ask for transcripts, a writing sample, and recommendations from people who have seen your research habits. Choose a program for the faculty who work on problems you actually want, and for the placement record of recent graduates. A famous name helps less than a supervisor who will read your drafts and introduce you to the kind of office you hope to enter.
During the degree, seek a research assistantship that produces a product with your name near it. Learn one statistical or archival toolkit deeply enough to be useful on a team. Present at a small workshop before you aim at a large conference. If government is the target, look for a fellowship or a summer detail inside an agency or a legislative research unit. Hiring managers in those offices want to see that you can write on a deadline for a reader who will not grade you, only use you.
Funding, city, and family all shape which degree is realistic. This guide will not invent costs or timelines. Read the offers the programs send, and compare the teaching load, the research support, and the kind of jobs graduates actually took. A doctorate aimed at a university career is a different bet from a master's aimed at an applied shop. Both are graduate degrees. They are not the same bet.
Government is the common employer
Many political scientists work for government. Federal agencies hire them into research, evaluation, and policy-analysis units. Legislative bodies keep nonpartisan research staff who answer official requests with written briefs. Statistical agencies and evaluation offices need people who can design a study and explain a limitation. State agencies do a smaller version of the same work on programs they run. The product is often a memo, a report, or a dataset documentation file, not a journal article, though the habits overlap.
Universities remain a major home for the doctorate: teaching, publishing, and advising. Research organizations and think tanks hire people to produce reports a funder or a public audience will read. A few political scientists work inside consulting firms that evaluate public programs. When you look at postings, read the product they name. A role that says "original research and a public report" is this career. A role that says "win the next election" is the other one. Apply where the product matches the training.
Getting hired in government means learning the application's rituals: a resume that lists methods and products, a writing sample cleared for release, and patience with a long process. Veterans' preference, citizenship rules, and security reviews apply to many federal jobs. Read those rules on the posting itself. In a university search, the writing sample is the paper, and the job talk is a lecture about your research. In both markets, vague claims about "passion for politics" lose to a specific project you finished.
From assistant on a project to lead on a brief
Early roles are assistant roles even when the title sounds grand. You clean data, check citations, draft a literature section, and sit in the meeting where seniors decide the outline. Do that work so the lead author does not have to redo it. Keep a log of methods you have used and of reports that shipped. The log becomes the proof that you can be trusted with a section of your own.
The middle of the career is leading a study or owning a recurring brief. You set the design, you manage the calendar, and you are the person who answers when a director asks what the finding does not support. That last skill is the one that gets you invited back. Senior political scientists choose the problems the office will spend a year on, review other people's designs, and represent the shop to outsiders. Management, if you want it, means budgets, hiring, and review cycles. Staying as a senior individual researcher is a respected path in many government offices and in many universities.
Pay moves when the work becomes harder to replace: a method few colleagues have, a subject the agency must cover, or a record of briefs that leadership actually used. Publishing helps in universities and in research organizations. In an agency, a clearance-friendly track record and the trust of a program office can matter more than a journal line. Know which market you are in before you spend a year on the wrong kind of proof.
The occupational wage figures
These amounts are Occupational Employment and Wage Statistics, May 2025, for Political Scientists. Entry pay is $83,350. The national median is $142,080. The distance from entry to the median is $58,730. That gap is large enough to cover the difference between a new research assistant's offer and the middle of the occupation, so label an offer before you celebrate or worry. A first job near the entry figure can be coherent. A job that already asks you to lead a study should be closer to the median.
The high end of the published range in the District of Columbia is $195,190. That high end differs from a median. No state median is listed with these figures, so the District of Columbia number should not be described as a typical wage for the city, and no other state's median should be filled in from memory. The distance from the national median to that high end is $53,110. Use $195,190 only when you mean the top of the published range in the District of Columbia.
What is listed, and what is absent
Listed: entry $83,350, national median $142,080, and the District of Columbia high end $195,190. Absent: state medians. The $58,730 and $53,110 gaps connect the listed points. They do not create a median for the District of Columbia or for any other place.
Government employment is common in this occupation, and a large share of senior research jobs sits in the capital, which is why a District of Columbia high end appears at all. Presence of that high end still differs from a median. An offer in the capital can land anywhere relative to $142,080. You only know where it lands by reading the offer, not by assuming the high end is the going rate.
Bringing the figures into a hiring talk
If the offer is near $83,350, talk about the path toward $142,080. Ask what a promotion requires: a finished degree, a study you led, or a grade level the personnel system already defines. The $58,730 step is too big for a shrug. In a government grade system, ask which grade the job is and which grade the next job is. In a university or a research organization, ask how salary reviews use outside offers and internal equity. You want the rule, not a compliment about your potential.
If the offer is near the national median, the next conversation is scope. Leading a brief, supervising junior researchers, or holding a subject the office cannot easily replace are reasons to discuss movement toward the high end. That movement is $53,110 on the published figures, and only if you are talking about the District of Columbia high end rather than a median that was not published. Say the label out loud. Median and high end are different statistics. Using the wrong one makes a fair capital-city offer look cheap or a stretched offer look ordinary.
When a recruiter quotes $195,190, ask whether they mean the high end of the published range in the District of Columbia. Then ask what share of that number is base pay. Research jobs sometimes fold in summer salary, consulting days, or a grant that ends. The published high end does not itemize those pieces. Neither does the national median. Keep the base, the term of the appointment, and the published landmark in separate sentences so you can see which dollars survive a year from now.
Relocation talk has to stay honest about missing medians. You can compare an offer with $83,350 and with $142,080 anywhere in the country, because those two are national. You can mention $195,190 only as the District of Columbia high end. You cannot cite a state median from this set, because none was provided. Housing costs and a partner's job sit outside the wage release. Use the three published figures for what they are, and use the employer's written offer for everything else.
The top of Political Scientist pay — and how to get there with AI
$195,190what Political Scientist pay reaches in District of Columbia
Highest state-level top-of-range annual wage for Political 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 — Chief Executives — reaches $772,840 in Oregon.
$83,350entry$142,080middle$195,190top end
The doctorate gets a political scientist into the field; what separates the upper end of this range is the second qualification stacked beside it, whether that is a methods specialization, a clearance, a regional language or a legal credential.
The core is common property among everyone with the same training: developing and testing theories from interviews, case law, historical papers, polls and statistical sources, interpreting legislation and the operations of governments, forecasting political and economic trends, teaching political science and serving on committees. Scarcity lives one step to the side. The employers paying at the upper end — federal agencies, contractors, litigation research shops and institutes clustered around the District of Columbia — want the political scientist who also carries a causal-inference toolkit, or eligibility for a clearance, or working Mandarin, or a bar admission. Each of those is a defined and obtainable thing, and study support from a model makes the second qualification cheaper to earn than the first ever was.
Your playbook, by where you are now
Just startingChoose the second thing early
Pick one adjacent qualification, advanced quantitative methods, a regional language or a legal credential, and schedule it inside your programme instead of after it.
Get to production standard in IBM SPSS Statistics and one scripting environment, not merely enough to survive a seminar.
Attend the methods institute your subfield respects and finish it with a replication you can show anyone.
Work through the reading list for that second field in NotebookLM, then test yourself against the primary sources rather than the summary.
What proves it: A methods certificate or language qualification completed alongside the degree itself.
Realistic span: during graduate study
A few years inMake the pairing impossible to miss
Publish one piece that only somebody holding both qualifications could have produced.
Apply early for posts requiring a clearance, since processing time is the real barrier and eligibility outweighs another working paper.
Build a working pipeline for election results and public opinion survey data that colleagues actually run.
Present to practitioner audiences as well as academic ones, because that is where the paying employers are listening.
Serve on the committees that touch hiring and funding, so the pairing is known to the people who allocate both.
What proves it: A published piece plus an appointment that required both qualifications.
Realistic span: the first five years after the degree
ExperiencedTrade on the combination itself
Take the roles written for the pairing: expert testimony, legislative drafting analysis, country risk, litigation research.
Negotiate on the scarcity of the combination rather than on years served or publication count.
Build and direct a research programme, so supervision and committee service buy influence instead of only consuming time.
Keep forecasting on the record, since a documented track record on political and economic trends is what practitioner clients actually buy.
Move toward executive direction of an institute or an agency unit, which is where this discipline's top end sits.
What proves it: An appointment whose written requirements name both of your qualifications.
Realistic span: eight years and up
The next 90 days
Spend a fortnight reading job advertisements you are not applying for. Take thirty postings from agencies, contractors, institutes and consultancies that pay above your current band, and tabulate what they demand beyond the doctorate. The same handful of items will repeat: a named statistical competence, clearance eligibility, a language, a legal qualification, a regional specialisation. Pick the one you would least resent spending two years on, then find the exact route to it — the institute, the examination, the sponsorship — and put a start date in your calendar. A political scientist who is only a political scientist is competing against everyone with the same training; the pairing is what removes most of that competition.
Wage figures: BLS OEWS, May 2025. 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 two AI wins for a political scientist: synthesizing the literature and coding text at scale. Open Elicit or Consensus to survey findings across hundreds of papers with citations, and use ChatGPT or Claude to draft, sharpen, and stress-test arguments. Verify every source in Google Scholar or the original — these tools still fabricate references.
For empirical work, pair GitHub Copilot or Cursor with R or Python to write and debug your analysis, and learn to use LLMs to classify and annotate text — speeches, legislation, manifestos, media — a method transforming empirical political science. Keep any confidential or human-subjects data out of consumer tools; reserve them for public texts and drafting.
The one rule, forever: Method and neutrality are your credibility. LLMs hallucinate citations, invent data, and carry political bias — verify every reference, never let AI fabricate or 'fill in' survey responses or results, and validate any AI text-coding against a hand-labeled sample with reported reliability. Protect human-subjects and IRB commitments: never paste confidential interview, respondent, or restricted-access data into a consumer tool, and disclose AI use per journal and funder policy.
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
Code text at scale with LLM annotation
Why this pays: Hand-coding thousands of documents used to take a team a semester; LLMs do a validated first pass in hours. That unlocks larger-N text studies — the novel, publishable empirical work that builds a tenure case or a consulting reputation.
ChatGPT / Claude (API)quantedaspaCy
1
Use an LLM (via the API for batch jobs) to classify or annotate a corpus — sentiment, topic, frame, position — then process and analyze in quanteda or spaCy in R/Python.
2
Build a rigorous, replicable coding scheme first.
Copy-paste this prompt
I'm doing a text-as-data study coding [e.g., congressional floor speeches] for [construct, e.g., populist rhetoric]. Draft a precise codebook with definitions, decision rules, and edge cases; write the classification prompt I'd give an LLM to apply it consistently; and specify how to validate against a hand-coded sample (which reliability statistics to report).
Always validate LLM coding against a human-labeled subset and report reliability (e.g., Krippendorff's alpha); never present unvalidated AI labels as data, and watch for the model's political bias.
What you'll haveLarge-N text analyses that were previously infeasible — the original empirical contributions that drive publications and reputation.
2
Synthesize the literature and the policy record
Why this pays: Whether you're writing a lit review, a grant, or a policy brief, comprehensive-and-fast beats slow every time. AI research tools map a field — and the policy documents that cite it — in an afternoon, feeding more publications, funded proposals, and the authority that commands senior pay.
ElicitConsensusOverton
1
Use Elicit or Consensus for the scholarly literature and Overton to see which policy documents, think tanks, and governments cite a body of work — evidence of real-world impact for grants and tenure.
2
Get a structured, cited synthesis and the open question.
Copy-paste this prompt
Synthesize the empirical literature on [e.g., the effect of vote-by-mail on turnout] from the last 15 years: the main findings, where they conflict, the methods used, the strongest studies, and the biggest unanswered question. Provide citations I can verify, and flag any consensus that rests on weak identification.
Verify every citation and finding in the original paper — AI research tools miscite and overstate consensus, and the review's credibility is yours.
What you'll haveA comprehensive, cited map of a field and its policy footprint in hours — the foundation for stronger papers and funded proposals.
3
Accelerate quantitative and survey analysis
Why this pays: Cleaner, faster empirical work means more studies and fewer errors — and well-identified, error-free results are what clear top journals and land in influential reports. AI coding assistants remove the data-wrangling drag so you produce more, better analysis.
GitHub CopilotCursorR / Python
1
Use Copilot or Cursor to write and debug R/Python for cleaning survey data (ANES, V-Dem, CES), running models, and producing publication-quality tables and figures.
2
Design and sanity-check an identification strategy.
Copy-paste this prompt
I want to estimate the effect of [treatment, e.g., a policy change] on [outcome] using [dataset]. Recommend appropriate identification strategies (DiD, RDD, IV, matching), the assumptions each requires and how to test them, robustness checks a reviewer will demand, and a code skeleton in R for the strongest option. Note the threats to inference.
AI can suggest and code a method, but the causal-inference judgment is yours — never trust an AI-proposed identification strategy without checking its assumptions against your data and design.
What you'll haveMore analyses, cleaner code, and better-identified results — the empirical rigor that gets work into top journals and reports.
4
Turn research into briefs, op-eds, and testimony
Why this pays: Influence — not just publication — earns a political scientist a think-tank fellowship, media presence, and consulting income. AI helps you rapidly repackage a finding for policymakers, editors, and the public, multiplying your reach without diluting the rigor.
ClaudeChatGPTPerplexity
1
Use Claude or ChatGPT to translate a paper into a 2-page policy brief, an op-ed pitch, and congressional-testimony talking points tuned to each audience.
2
Make a rigorous finding land with a non-academic reader.
Copy-paste this prompt
Turn this research finding [paste your public abstract/result] into a 700-word op-ed for [outlet]: a clear hook, the finding in plain language, why it matters for policy now, honest caveats, and a specific takeaway for decision-makers. Non-partisan tone, no overclaiming.
Keep it non-partisan and within what your evidence supports — overclaiming for a headline destroys the scholarly credibility that makes you worth citing and hiring.
What you'll haveResearch that reaches policymakers and the public — the visibility and influence behind fellowships, media, and consulting income.
5
Build a data-driven forecasting and consulting edge
Why this pays: The best-paid political scientists often work beyond pure academia — polling, campaigns, risk analysis, tech policy — where quantitative forecasting and rapid analysis command premium fees. AI lets you build models and turn raw political data into decision-ready products fast.
Python (Copilot)ClaudePerplexity
1
Use AI-assisted Python to build forecasting and scenario models (elections, legislative outcomes, geopolitical risk) and Perplexity to pull current, sourced context fast.
2
Package the analysis as a client-ready decision product.
Copy-paste this prompt
Act as a political-risk analyst. From this situation and data [describe the public political question and inputs], produce a decision memo for a [client type]: a base-rate-informed forecast with a probability and confidence, the key drivers and assumptions, scenarios with triggers to watch, and clear implications. Flag where the evidence is thin.
State probabilities and assumptions explicitly and separate analysis from advocacy; never present a model's output as certainty, and disclose the limits of the data.
What you'll haveDecision-ready forecasts and memos clients pay premium rates for — the outside income and profile that reach the top of the band.
Your 12-month sequence to the top of the range
How the plays above stack into a path from median pay toward the $195,190 tier.
Month 1
Wire Elicit/Consensus into your literature workflow and Copilot into your R/Python; start drafting with Claude, verifying every citation.
Months 2-3
Run one LLM text-coding pilot with a validated codebook and reliability checks.
Months 3-6
Accelerate a quantitative project with AI and repackage a finding into a policy brief or op-ed.
Months 6-12
Build a forecasting or consulting product, and use Overton to document your work's policy impact for grants and promotion.
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.
Same live O’Reilly 3rd already on data-scientist / python-developer / market-research-analyst. This leftover page says pair GitHub Copilot or Cursor with R or Python to write and debug your analysis; Month 1 is Wire Elicit/Consensus into your literature workflow and Copilot into your R/Python. 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 4:36 PM PT.
Next steps for a Political 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.
Political Scientist work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Political Scientists (SOC 19-3094). 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 areas include Law and Government and History and Archeology; the links search those subjects, not a generic 'career courses' list.
Political Scientists in this dataset list IBM SPSS Statistics among the tools in use, so a program that names that stack is a better fit than a survey course.
Coursera search for law and government — a graduate-level or professional certificate that lines up with science, 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 Political Scientist work, not a claim that they list a counted SOC 19-3094 inventory.
Write a Political Scientist resume, or one aimed at Chief Executives, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.
A Political Scientist resume that names the actual tasks on this page, or the step-up title Chief Executives, beats a blank template when you apply.
What Political Scientists earn by state
This page does not show a state table, and the reason is worth stating: the Bureau publishes this occupation nationally, but fewer than five states employ enough people in it to report a median we would stand behind. 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 $83,350, the median is $142,080, and the top of the range is $195,190. Those national figures come from U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025.
No — AI can code text and run models, but it can't build a theory, defend a causal claim, judge the political stakes, or take responsibility for advice that shapes policy. Those are the core of the job and grow more valuable as data scales. Political scientists who use AI produce more and reach further; the methods, judgment, and neutrality stay human.
Can I use an LLM to code my data or as a survey respondent?
For coding text, yes — but only with a validated codebook and reliability reported against a human-labeled sample; unvalidated AI labels aren't data. Using LLMs as synthetic survey respondents is an active, contested research area, not a substitute for real data — treat it with deep caution and full disclosure.
How do I keep AI's political bias out of my work?
Assume it's there. LLMs carry measurable partisan and cultural biases, so never rely on one for substantive judgments, validate all classifications against human coding, test prompts for sensitivity to wording, and keep your own analysis non-partisan and transparent. Bias-checking is part of the method now.
Is it safe to put my interview or survey data into ChatGPT?
Not confidential or human-subjects data. IRB commitments and respondent confidentiality prohibit pasting identifiable or restricted data into consumer tools. Use only public texts and de-identified drafts, keep protected data in approved systems, and follow your institution's data policies.
How does AI actually raise a political scientist's pay?
By multiplying both output and influence: more publications and funded grants from faster research, plus briefs, media, and consulting that turn scholarship into real-world impact. Those earn tenure, fellowships, and the well-paid roles in polling, consulting, and tech policy at the top of the band.
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.