PayCrunch Research · The exact AI playbook for your profession, sourced to the U.S. Bureau of Labor Statistics

PayCrunch AI Playbook · Finance

The hedge fund analyst who owns the desk's plumbing

$291,570estimated top of the range · middle $125,000 / yr
AI augments this role

Hedge Fund Analysts in the United States earn a median of $125,000 a year. Pay starts near $75,000. The top of the range is estimated at $291,570. The Bureau of Labor Statistics does not publish a separate wage series for this exact title, so this figure is derived from the closest occupation it does track and is labelled an estimate.

Source: PayCrunch estimate. Last checked 9 September 2026.

Entry level
$75,000
Top-end estimate
$291,570
Education
Bachelor's degree in Finance; MBA valued
Lower disruption Higher exposure AI augments this role
Entry · $75,000 Top-end estimate · $291,570 Middle $125,000

Wages — PayCrunch estimate. The Bureau of Labor Statistics does not publish a separate wage series for Hedge Fund Analyst; figures are derived from the closest occupation it does track and are labelled as estimates. AI-impact rating is PayCrunch's editorial assessment. Updated September 2026.

🆕 New & Trending AI Tools for Hedge Fund AnalystReviewed September 2026

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

NumericNEWPaid / see site

AI-driven month-end close, reconciliation, and reporting.

How a Hedge Fund Analyst uses it: automate reconciliations and close the books faster

HebbiaNEWEnterprise / see site

AI that reads and analyzes large financial documents and filings.

How a Hedge Fund Analyst uses it: pull answers out of contracts, filings, and reports in minutes

NotebookLMNEWFree / $7.99 mo

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

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

MindBridgeEnterprise / see site

AI that scans transactions for anomalies, errors, and fraud risk.

How a Hedge Fund Analyst uses it: flag risky or unusual entries across the whole ledger, not just a sample

Vic.aiEnterprise / see site

Autonomous accounts-payable and invoice processing.

How a Hedge Fund Analyst uses it: let AI code and process invoices with minimal manual entry

RampFree core / paid

Finance platform with AI that automates expenses and spend controls.

How a Hedge Fund Analyst uses it: auto-categorize spend and catch policy issues in real time

Power BI Copilot$10+ mo

Microsoft analytics with AI that builds dashboards and explains trends.

How a Hedge Fund Analyst uses it: ask questions of financial data and get charts and forecasts back

ChatGPTFree / $20 mo

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

How a Hedge Fund Analyst uses it: draft emails and documents, summarize long files, and get instant answers to on-the-job questions

ClaudeFree / $20 mo

AI assistant known for careful writing, long-document analysis, and coding.

How a Hedge Fund Analyst uses it: analyze big reports or spreadsheets and turn messy notes into clean, finished writing

The memo on the portfolio manager's desk

A hedge fund analyst, in the job people actually hire, writes research memos. The reader is a portfolio manager or a senior analyst inside the fund, not a stranger looking for a tip. You gather public information on a company, a sector, or a theme the fund already cares about. You write what changed, what is uncertain, and what would have to be true for the fund's existing view to need an update. The manager decides what the fund does. Your name on a memo gives you no licence to tell outsiders what to own, and personal tips sit outside this career.

The memo has a shape the desk can reuse. A short header that says which name, which question the manager asked, and the date. A body that separates facts you can point to in a filing or a transcript from judgments you are willing to defend. A close that says what you still do not know. Analysts who blend those layers make the manager do the sorting. Analysts who keep them apart get asked for the next memo. Style does real work. A muddy memo is a risk the fund did not mean to take.

You will sit in the meeting where that memo is used. Bring the source, not a vibe. If a number in your note comes from a filing, know the page. If a point came from a call the firm authorized, know who was on it and what they actually said. If you were wrong last month, say so before someone else does. Funds remember the analyst who updates a view when the facts move. They remember, less kindly, the analyst who defends a paragraph because changing it would feel like losing.

Filings, calls, and the afternoon rewrite

A research day starts with what landed overnight: a filing, an earnings transcript, a news item the desk flagged, a data series the fund already licenses. You read before you write. You check whether the new fact touches a memo you filed last week. You tell the manager early if it does, even when the rewrite will be annoying. Surprise at the end of the day, about a fact that was public at dawn, is a credibility problem. The tools are ordinary: the filings themselves, a spreadsheet that organizes figures you can trace, notes from calls, and the fund's own archive of prior memos.

Calls, when the firm uses them, follow the firm's rules. You do not freelance a conversation with someone who owes the company a duty of silence, and you do not treat a rumor in a chat as a source. If the fund has a compliance officer, that person is part of your process, not an obstacle to route around. Write down what was said in language the speaker would recognize. A paraphrased "they basically told me" is how memos pick up facts that were never stated. The portfolio manager can survive a dull, accurate note. A colorful, loose one is harder to unwind.

Models, if your desk uses them, are a way to keep public figures consistent. They are not a machine that owes the fund a result. When a model and a filing disagree, the filing wins until you understand the gap. You will be asked to change an assumption and show what moves. Do that plainly, and label the assumption as an assumption. The career is research writing under time pressure. Trading instructions sit outside that routine, and nothing in the day asks you to recommend a personal investment to a friend, a relative, or a reader outside the fund.

A FINRA registration, only when the firm requires one

Some firms require a FINRA registration before an analyst does work the firm has tied to that registration. FINRA grants the registration. The organization's site is finra.org. Held properly, the registration shows you completed the registration that firm assigned. It is a registration. People prepare through the firm's own process and through whatever FINRA lists for that registration at the time. Many research seats never involve one. A memo job can be the whole role. Ask the fund, before you imagine a stack of credentials, whether a FINRA registration applies to the chair they are filling.

A separate, voluntary path some analysts pursue is the charter offered by the CFA Institute. That charter shows you finished the institute's program. That charter and a FINRA registration are different credentials, and a fund that never asks for either one may still hire you on the strength of your memos and your references. Read the institute's current eligibility if you want the charter. Read FINRA's current description if the firm names a registration. Mixing the two in an interview, as if they were one badge, tells a hiring manager you have not looked at the actual seat.

Compliance is the daily face of whichever registration or policy the firm uses. Personal accounts, if you have them, follow the firm's rules on what you may hold and when you may trade for yourself. Those rules exist so the fund's research and your private life do not blur. Ask for the policy in writing during the offer, and follow it. An analyst who treats the policy as paperwork for other people will not last, and should not. The memo can be brilliant and the job can still end over a personal account.

Ask whether a registration applies

A FINRA registration may apply at some firms and never come up at others. Name it as a registration. Let the fund tell you if the seat requires one, and keep research memos as the work you are offering.

Junior support, a coverage list, a senior chair

Most people enter as a junior. You build charts a senior asked for, you summarize a filing, you sit in the meeting and take the note, and you learn how that fund likes an argument to look. The step up is a coverage list of your own: names you follow, memos you sign, and a manager who will tell you when the work is thin. Senior analyst is the seat where your view carries more of the meeting. Some seniors later become portfolio managers. That move is a different job. It adds decision-making for the fund's capital. A longer memo with a new title misses that change, and not every excellent analyst wants it.

The fund's style shapes the path more than the industry slogan does. A single-manager fund may want deep memos on a short list of companies. A multi-manager platform may want faster work, tighter risk conversations with a team lead, and less patience for a beautiful essay. A credit desk and an equity desk share the memo habit and differ in the documents they live in. Apply to the desk whose documents you are willing to read for years. Switching later is possible. Pretending on day one that every desk is the same will make the first year feel like a mistake you could have avoided.

Leaving the fund for a company, a bank research role, or a different fund is common. Take your memos only in the form the compliance policy allows. The skill that travels is clear writing tied to sources, plus the habit of saying what you do not know. The skill that does not travel is gossip about positions. You can describe your process in an interview without describing the fund's book. Do that. A candidate who arrives with tales of what the last fund owned is a candidate the next fund should be afraid to hire.

What the desk reads before it meets you

Send a writing sample you are allowed to share. A school project labeled as a school project is fine. A memo that includes material the last employer owns crosses a line. The sample should show a fact, a source, and a judgment kept in separate sentences. We, meaning a hiring manager on a research desk, look for whether you can be wrong in public inside the note: "this rests on an assumption, and here is what breaks it." Candidates who only send victory laps are harder to trust with a live name.

The conversation will walk a company or a filing. You may be handed a document and asked what you notice. Start with what is on the page. Say what you would check next. Resist the urge to leap to a dramatic conclusion so you sound decisive. Decisiveness in this job is a sourced sentence, not a loud one. If you do not know a term, say so. Looking it up later is a strength. Inventing a definition in the room is how small errors become memos.

Ask how many names a junior covers, who edits the memo, and whether a FINRA registration is part of the seat. Ask how pay is split between the figure in the offer and any variable amount the firm describes, and get that description in writing. A large possible variable with no history and no formula is a story. A clear formula you can read is a term of employment. Compare both with the estimates below before you resign anywhere. The week matters too: who you support, whether you are on a single desk, and what "urgent" has meant in the last month. Urgent every day is a staffing fact, not a personality test.

Estimated pay for a title without its own series

Treat these dollars as PayCrunch estimates. The Bureau of Labor Statistics does not publish a separate wage series for the hedge fund analyst title, so none of the figures should be described as a published series for this exact job. Entry is $75,000. The median estimate is $125,000. The estimated top is $291,570. The gap from entry to the median is $50,000. The gap from the median to the estimated top is $166,570. Use those figures when you negotiate. A number from a different finance title does not become this estimate because the office looks similar.

A first seat near $75,000 should come with a plain account of how pay can move across the $50,000 gap toward $125,000. Coverage of your own names, a finished year of memos the manager will defend, or a step the firm has written down are real accounts. "We pay well if we do well," with no definition, fails as an account. An offer already near $125,000 is a conversation about scope: how many names, how much of the meeting is yours, and what variable pay, if any, sits beside the estimate. The $166,570 stretch from $125,000 to $291,570 is the long part. It belongs to a discussion of a senior seat or a year the firm itself treats as the top of this title, not to a junior who has just learned the archive.

Write the offer, $75,000, $125,000, and $291,570 on separate lines. If the firm describes variable pay, write that description beside the estimate rather than inside it. These figures do not itemize a bonus, and you should not invent one to make the top look nearer. Ask what happened for people who joined in the seat you are taking, in words the firm will stand behind. Then decide whether the week matches the line you are being offered. A median-level research job with a humane edit process can be a better life than a number aimed at $291,570 in a shop that burns through juniors.

Once you are inside, bring the same three figures to a review. If you now sign memos and your pay remains on the entry side of the $50,000 gap, you have a specific sentence. If you are near $125,000 and you want the responsibility that might point toward the estimated top, name the coverage and the meetings you already carry, and keep $291,570 labeled as the estimated top. The registration, if your firm uses one, stays a registration. The work that moves pay is the memo: sourced, revised when the facts change, and useless as a personal recommendation to anyone outside the fund. The estimates keep the dollars tied to a title the Bureau does not publish on its own.

The top of Hedge Fund Analyst pay — and how to get there with AI

$291,570top-end estimate for Hedge Fund Analyst

PayCrunch estimate - derived from the closest occupation BLS tracks (Financial and Investment Analysts, 13-2051). This figure is PayCrunch’s estimate, not a Bureau of Labor Statistics published wage for this exact title.

And the role it leads to — Financial Managers — reaches $370,780 in New York.

$75,000entry$125,000middle$291,570top end

Hedge fund analysts paid at the top of this range are not the fastest at securities valuation; they are the ones whose pricing and screening tooling everyone else on the desk now runs on.

Monitoring economic, industrial and corporate developments across financial publications, government sources and company interviews used to be a full week of reading. Models compress that reading, and query layers over Apache Hive or Apache Pig compress the data pulls behind it. What changes pay is who owns the compression. An analyst who keeps a private pricing spreadsheet stays a producer of notes. The one who turns securities valuation and screening into something a portfolio manager and three colleagues open daily becomes part of the desk's infrastructure, and that is a different conversation about pay.

Your playbook, by where you are now

Just startingMake one screen other people borrow

  1. Rebuild one valuation from primary sources in Microsoft Excel until every input has an origin you can name out loud.
  2. Move the repetitive data pull into Alteryx software so a screen refreshes without you touching it.
  3. Keep a dated file of every recommendation you make on investments and on timing, and score it later against what happened.
  4. Ask Claude to list the assumptions your valuation leans on hardest, then stress the two that move the answer furthest.

What proves it: A screen or valuation sheet a colleague opens without asking you how it works.

Realistic span: The first eighteen months.

A few years inTurn the sheet into shared plumbing

  1. Put the desk's common data into Microsoft Access or a business intelligence layer so five people stop keeping five versions.
  2. Automate the materials you prepare for transactions so deal packets assemble from the same source as the model.
  3. Run positions through Advanced Portfolio Technologies Simulator and write up which scenarios the book actually survives.
  4. Learn one specialised mandate properly, socially responsible funds and green exchange-traded products among them, and become the person asked about it.
  5. Have Perplexity gather background on an unfamiliar industry, then verify every figure against a primary source before it enters a report.

What proves it: A tool with named users on the desk and a written note of what it replaced.

Realistic span: Roughly years two through five.

ExperiencedOwn the process, then the people

  1. Present written and oral reports on industry trends where you answer for the call, not only for the arithmetic.
  2. Train and mentor junior team members on the tooling so its upkeep stops being one person's evening job.
  3. Choose deliberately between a portfolio seat and the financial management track this experience feeds.
  4. Weigh geography with open eyes: South Dakota sits at the top of this occupation's range, and fund administration clusters there for reasons worth understanding.

What proves it: A production process that keeps running correctly through a fortnight you are away.

Realistic span: Year six and beyond.

The next 90 days

This quarter, pick the single thing you repeat most as a hedge fund analyst, the comparables refresh, the morning monitoring sweep, the pricing check before a trade, and rebuild it as something two other people can run. Write down what it costs you in hours today. Move the data pull into Alteryx software or a query you can rerun, put the logic somewhere a colleague can read it, and write half a page of instructions in Google Docs. Then hand it over and watch where they get stuck. The hours you free are yours to spend on original work, and the tool is what your name gets attached to when scope is handed out.

Wage figures: PayCrunch estimate. The playbook is PayCrunch editorial guidance, not a guarantee of pay or placement.

Careers related to Hedge Fund Analyst

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).

Start with AI-powered document search. Open AlphaSense or Hebbia and ask a real research question across filings, transcripts, and broker research — it surfaces and cites the exact passages in seconds instead of you reading 200 pages. You still read the source it points to; the AI just gets you there faster.

For modeling and general reasoning (no MNPI, no proprietary positions), use ChatGPT's data-analysis mode or Claude to sanity-check a model, summarize an industry, or draft a bear case. Keep anything material or non-public inside approved systems, and verify every figure against the primary filing.

The one rule, forever: The line that ends careers is material non-public information. Never input MNPI, expert-network notes, or anything under NDA into a public AI tool, and never let AI output substitute for compliance. Verify every number an AI gives you against the primary source (the actual 10-K or press release) before it enters a model or memo — a hallucinated figure in an investment thesis is a real trade on false data. Keep proprietary positions and models out of consumer tools.
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
Compress the reading with AI document intelligence
Why this pays: Alpha is partly a speed game — the analyst who extracts signal from filings and calls fastest has more time for the thinking that generates ideas, and more ideas is more PnL.
AlphaSenseHebbiaBloomberg (Document Insights)
1
Use AlphaSense or Hebbia to search across a company's filings, transcripts, and broker research, asking pointed questions and reading the cited passages it returns.
Copy-paste this prompt
Across [Company X]'s last 8 earnings calls and 10-Ks, find and quote every management comment about [pricing power and gross-margin trajectory]. Note how the language changed over time and flag any shift in tone or guidance. Give the exact source and date for each quote.
Use to locate evidence fast; read the cited primary source yourself before you trust it, and keep the queries within compliance.
2
Build a running, dated evidence file per name so your thesis is traceable to sources, not memory.
What you'll haveThe same coverage in a fraction of the time — more names, deeper work, and the idea flow that drives a top-of-range bonus.
2
Automate the financial-model plumbing
Why this pays: Hours spent hand-keying financials from filings are hours not spent on the thesis; automating extraction is a direct multiplier on how many models you build and maintain.
DaloopaChatGPT (Advanced Data Analysis)Excel / Python
1
Use Daloopa to pull historicals straight from filings into your model, and ChatGPT's data-analysis mode to check formulas and run scenarios on data you provide.
Copy-paste this prompt
Here is [Company X]'s segment revenue and margin history [paste sanitized public data]. Build a driver-based 3-statement projection: let me set assumptions for [revenue growth, gross margin, opex leverage], and output revenue, EBIT, FCF, and a simple DCF. Show the formulas and flag where my assumptions most affect the valuation.
Use on public data to build and stress-test models; verify every historical against the actual filing and own the assumptions.
2
Run bull/base/bear scenarios and a sensitivity table so you understand what the market is actually pricing in.
What you'll haveMore models, built and maintained faster and stress-tested harder — the analytical throughput behind bigger, better bets.
3
Pressure-test your thesis and find the variant perception
Why this pays: Alpha comes from being right when consensus is wrong; using AI as a relentless bear/bull sparring partner sharpens the differentiated view PMs pay for.
ClaudeChatGPTPerplexity Finance
1
Write your thesis, then have Claude argue the other side as hard as it can — the strongest bear case for your long — so you find the holes before the market does.
Copy-paste this prompt
Here is my long thesis on [Company X]: [paste, public info only]. Steelman the bear case: the three most credible reasons this loses money, what data would confirm each, what the bulls are structurally underweighting, and what would have to be true for consensus to be right and me wrong.
Use to stress-test on public information; the investment judgment is yours, and keep any non-public research out of the tool.
2
Use Perplexity Finance to scan for disconfirming evidence and recent developments you might have anchored past.
What you'll haveTheses that survive their own strongest counterargument — the differentiated conviction that generates alpha and bonus.
4
Turn unstructured signals into structured data
Why this pays: Edge increasingly comes from alternative and unstructured data; the analyst who can wrangle it with light AI and code finds signals others miss — and that is directly rewarded.
ChatGPT / Claude (Python)Bloomberg / FactSetTegus / AlphaSense
1
Use AI to write short Python to parse permitted public alt-data (job postings, app rankings, pricing pages) into a time series you can chart against the stock.
Copy-paste this prompt
Write Python to take [a company's monthly count of open engineering roles that I provide] and plot the trend against [quarterly revenue]. Explain what a hiring acceleration or deceleration might signal and the limits of this as an indicator.
Use only public, permitted data sources; validate the signal's history before trading on it, and confirm it is compliant.
2
Correlate the alt-data series with fundamentals and treat it as one input, not a crystal ball.
What you'll haveProprietary-feeling signals from public data — the differentiated edge that separates a top analyst from the pack.
5
Produce sharper research memos and PM pitches
Why this pays: Analysts are judged on the quality and clarity of their ideas and how well they defend them; AI makes your written work tighter and your pitches better-prepared.
Claude / ChatGPTAlphaSense (Smart Summaries)PowerPoint
1
Draft your memo, then use Claude to tighten the argument, surface unstated assumptions, and prep the questions your PM will ask — you own every number and claim.
Copy-paste this prompt
Here is my investment memo draft: [paste, public info]. Act as a skeptical PM: list the 10 hardest questions you would ask, where the thesis is weakest, what position sizing and risk/reward you would want to see, and what would make you pass. Then suggest a tighter one-paragraph pitch.
Use to sharpen and rehearse; verify all figures against primary sources and keep non-public details out of the tool.
2
Build the risk/reward and position-sizing case explicitly — PMs fund ideas that come with a plan, not just a view.
What you'll haveClearer memos and pitches you can defend under fire — the credibility that gets your ideas sized and gets you promoted toward a book.
6
Monitor your book and the tape automatically
Why this pays: Catching a thesis-changing development first protects PnL and builds the PM's trust — the trust that leads to more capital and a bigger share of the upside.
AlphaSense / Perplexity (alerts)BloombergChatGPT
1
Set AlphaSense and Bloomberg alerts on your names for the specific catalysts and risks in your thesis, and use AI to summarize overnight developments before the open.
Copy-paste this prompt
Summarize any material developments in the last 24 hours for these tickers: [list]. For each, tell me whether it affects the core thesis (pricing, competition, regulation, guidance), the likely direction, and what to watch next. Public news only; cite sources.
Use for a fast morning scan; confirm anything actionable against the primary source before you act, and stay within compliance.
2
Keep a thesis tracker per position (what would change your mind) and check developments against it, not against your hopes.
What you'll haveEarly awareness of thesis breaks and catalysts — the risk discipline that protects returns and earns you more capital.
Your 12-month sequence to the top of the range

How the plays above stack into a path from median pay toward the $220,000 tier.

Month 1
Adopt AI document search (AlphaSense/Hebbia) for your coverage and start a sourced evidence file per name.
Months 2-3
Automate model plumbing with Daloopa and use AI to stress-test formulas and scenarios on public data.
Months 3-6
Use AI as a bear/bull sparring partner on every thesis and start experimenting with alt-data signals.
Months 6-9
Sharpen memos and PM pitches with AI critique; build explicit risk/reward and sizing.
Months 9-12
Automate monitoring and morning prep across your book with alerts and AI summaries.
Year 2
Turn consistent, differentiated, well-defended ideas into a track record — the path to running capital and pay at the top of the range.
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.

CFA Institute 2026 CFA Program Curriculum Level I Box Set

Same live Wiley/CFA Institute 2026 Level I box set already on financial-analyst / investment-analyst / pension-fund-manager / credit-analyst. This page sources CFA Institute — investment profession standards & ethics. Not leftover 94 CFP (that is financial-planner / financial-advisor) and not Level II or Level III.

Next steps for a Hedge Fund Analyst

Some links below are affiliate or partner links. PayCrunch may earn a commission if you enroll or subscribe through them, at no extra cost to you. Wage figures on this page still come from the Bureau of Labor Statistics, not from these programs.

Hedge Fund Analyst work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Financial and Investment Analysts (SOC 13-2051). 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.

Hedge Fund Analysts in this dataset list Alteryx software among the tools in use, so a program that names that stack is a better fit than a survey course.

The next title this dataset points at is Financial Managers; a credential aimed that way is a clearer step than another year in the same seat.

Accounting And Finance programs on Coursera for Hedge Fund Analyst work

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

Accounting And Finance courses on edX

edX search for accounting and finance, aimed at business and finance (SOC 13-2051). Same field as the Coursera link, different university catalog.

Screened remote and flexible Hedge Fund Analyst 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 Hedge Fund Analyst work, not a claim that they list a counted SOC 13-2051 inventory.

Build a Hedge Fund Analyst resume on Resume Now

Write a Hedge Fund Analyst resume, or one aimed at Financial Managers, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.

Build a Hedge Fund Analyst resume on Zety

A Hedge Fund Analyst resume that names the actual tasks on this page, or the step-up title Financial Managers, beats a blank template when you apply.

What Hedge Fund Analysts earn by state

This page does not show a state table, and the reason is worth stating: the Bureau of Labor Statistics does not publish a separate wage series for this job title, so there are no official state figures to show. Scaling the national median by a cost-of-living index would produce a number for every state, but it would be an estimate of living costs wearing a wage’s clothes, and PayCrunch would rather show you nothing than that.

What the national figures say: pay starts near $75,000, the median is $125,000, and the top of the range is $291,570. Those national figures are a PayCrunch estimate, not a Bureau of Labor Statistics published wage for this exact title.

If you want to see how far state pay can move for jobs the Bureau does publish state-by-state, the best-paying state for every occupation is a free open dataset, and the salary-by-state statistics page summarises the pattern across all 824 of them.

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 hedge fund analysts?
No — but it raises the bar. AI does the reading and data extraction that used to be the junior analyst's whole day, so value moves decisively to judgment: variant perception, position sizing, knowing which questions matter, and defending an idea with real money on the line. Analysts who use AI generate more and better ideas; those who do not will be outworked by those who do.
Can I put a company's filing into ChatGPT?
Public filings, yes (though verify what it extracts). MNPI, expert-network notes, anything under NDA, or your fund's proprietary positions and models — absolutely not. That is both a compliance violation and a data-leak risk. Use approved, enterprise tools for anything material or non-public, and keep public and non-public workflows strictly separate.
Can I trust AI-extracted financial numbers?
Only after you check them against the primary source. AI transcription and extraction are fast but not infallible, and a wrong number in a model is a real trade on false data. Use tools like Daloopa that link back to the filing, and spot-check every figure that drives the thesis.
Does AI give me an edge if everyone has it?
The tools are commoditizing, so the edge is not access — it is what you do with the reclaimed time. Analysts who use AI to cover more names, build proprietary alt-data signals, and pressure-test theses harder generate differentiated ideas; those who just summarize faster do not. The edge is judgment applied at greater scale.
How do I get from analyst pay to the $220k+ top of the range?
Generate alpha the PM trusts and build a track record toward running your own book, where comp is tied to PnL. Use AI to widen your coverage, sharpen and defend your best ideas, and manage risk — consistent, differentiated, well-sized ideas are what turn into a bigger share of the upside.
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