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

PayCrunch AI Playbook · Finance

The mergers and acquisitions analyst who narrows down

$239,700top of the range in South Dakota · middle $102,740 / yr
AI is transforming this role

Mergers and Acquisitions Analysts in the United States earn a median of $102,740 a year. Pay starts near $63,720. Pay reaches $239,700 at the top of the range in South Dakota, the best-paying state for this work among those with at least 500 people in the job.

Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Financial and Investment Analysts, SOC 13-2051). Last checked 9 September 2026.

Entry level
$63,720
Top of the range · South Dakota
$239,700
Education
Bachelor's degree in Finance; MBA valued
Lower disruption Higher exposure AI is transforming this role
Entry · $63,720 Top of range · $239,700 (South Dakota) Middle $102,740

Wages — U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Financial and Investment Analysts). 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 Mergers and Acquisitions AnalystReviewed September 2026

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

NumericNEWPaid / see site

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

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

Assigned to a deal the team already opened

A mergers and acquisitions analyst does not open the process. The process is already alive when the staffing list lands. A company is exploring a purchase, a sale, or a combination, and a team of more senior people owns the relationship. The analyst is placed on that team to keep the work moving: numbers current, documents findable, and the internal story consistent from one meeting to the next. The drama people imagine, the handshake and the headline, sits above this seat. The seat itself is stamina, accuracy, and the ability to tell a senior colleague what changed since yesterday.

The week has a rhythm that follows the process, not a classroom calendar. Early on, you gather public information and the files the client has already shared, and you learn which version of the story the team is using. In the middle, requests arrive in bursts. Someone needs a page updated before a morning meeting. Someone else needs a figure traced back to the document that produced it. Late in a process the pace tightens, and small mismatches become urgent because other people are about to rely on them. You learn to say what you know, what you still need, and what you will not guess.

Employers are investment banks, boutique advisory firms, and the corporate development groups inside companies that buy other companies. A bank analyst may be staffed across more than one live process and may also support pitches the coverage team hopes will become live later. A corporate analyst often stays with one employer's strategy and sees fewer processes more deeply. The daily materials differ. The job is still deal staffing: you are on the team that is already working, and your output is what that team can stand behind.

Inherited models and a living data room

The model on your screen is usually one the team already owns. You did not invent its structure on a blank weekend, and you should not treat it as a private experiment. Your task is to keep it faithful. New figures arrive from a data room, from a management presentation, or from a file a client revised overnight. You put those figures where the team has already decided they belong, you check that the source and the model agree, and you save a version a colleague can audit. If something in the model surprises you, you ask the person who built it before you "fix" a result the team intended.

The data room is the other half of the job, and it is a place as much as a folder. Documents live there so the right people can read them without hunting through inboxes. You track what has arrived, what is still missing, and which follow-up is blocking a page the team needs. You keep names, dates, and versions straight. A sloppy room wastes senior time and creates the kind of contradiction that shows up in a meeting you are not even attending. A clean room lets an associate or a vice president find the support for a number without calling you at midnight, which is a quieter kind of success.

Around the model and the room, you assemble materials the team will actually use. Internal memos. Pages for a meeting that is already on the calendar. A comparison the group asked for, built from documents already in hand. This is description of the job, not a playbook for how a deal should be struck. You are not deciding strategy in this seat. You are making the team's existing strategy legible, sourced, and current. People who understand that boundary are trusted with more of the process. People who freelance a clever idea inside a live model create repairs.

Other professions sit around the same process, and your job is to work with them without becoming them. Lawyers handle the agreements. Accountants dig through the financial record. Consultants may show up with their own workstreams. You make sure the model and the room reflect what those people have actually provided, and you flag a mismatch when a figure in a memo and a figure in the model cannot both be current. You do not give legal advice, and you do not redesign the transaction from the analyst seat. You keep the shared facts in one place so the people who do own those decisions are looking at the same page.

The hours can be long when a process is hot, and they can ease when it pauses. A professional way to talk about that, in an interview or on the job, is specific. Which nights ran late because a data room dropped a new set of files. Which handoff you left so the person covering you could continue without reconstructing your work. Reliability is the reputation that matters. Brilliance that cannot be checked will not survive the next person who opens the file.

One analyst series in the May 2025 release

Pay for this seat comes from a wider occupational bucket. Occupational Employment and Wage Statistics, May 2025, report the figures under Financial and Investment Analysts. That shared name belongs in this pay discussion and then drops out. A newcomer meets a national entry of $63,720. The national median of $102,740 stands $39,020 above that entry. The high end of the published range is $239,700 in South Dakota, among places with enough people in the work for the Bureau to publish a high end. From the national median up to that high end, the distance is $136,960.

South Dakota's $239,700 is the high end of the range, and a state median is a different statistic entirely. The highest median in the set is New York's, at $127,930, which sits $25,190 above the national median. Oregon's median is $120,590. Massachusetts shows $111,040, California $109,110, and New Jersey $108,610. Between the highest state median and the lowest, the spread is $64,930. An offer in New York should be read against $127,930 long before anyone mentions a high end that lives in South Dakota. An offer that quotes $239,700 is quoting the top of a published range in that one place, not a typical analyst's pay and not New York's middle.

Keep the high end and the medians apart

$239,700 is South Dakota's high end of the published range. $127,930 is New York's median, the highest median in this set. Using one number as if it were the other will scramble a compensation talk before it starts.

Staffing choices on a coverage team

Banks and boutiques hire analysts from undergraduate programs in finance, economics, accounting, and related fields, and sometimes from other majors when the person can already show careful quantitative work. Internships matter because they show you have survived a live process, or at least a close imitation of one, without losing track of versions. Corporate development groups sometimes prefer a year or two in banking, audit, or another analyst seat first. In every case the hiring voice is similar. Can you keep a model honest. Can you keep a room organized. Can you write a page a senior person does not have to rebuild.

Interviews often include a conversation about a process you supported, with the confidential names removed. Describe your actual piece: the model you maintained, the data room you tended, the error you caught because a source and a spreadsheet disagreed. Skip any performance of tactics. The interviewer who does this work already knows you were not the person deciding whether a deal should happen. They want to know whether they can staff you on Monday and still trust the file on Wednesday.

A charter from the CFA Institute is an optional credential some analysts pursue, especially if they later move toward investment research or asset management. The institute grants it after its own program of study. It proves a broad grounding in investment analysis. It is not a requirement for a first staffing on a mergers team, and it does not teach the housekeeping of a data room by itself. If your employer is a broker-dealer, a registration the firm sponsors may also enter the picture. Treat that as the firm's compliance path, not as a puzzle to describe in an interview. Lead with the work you can already do.

Expect the hiring process to test composure as much as coursework. You may be asked to walk through a page you built, to explain where a number came from, and to revise it while someone watches. Treat that as a glimpse of staffing, not as a performance. Speak in sources. If you do not know, say what you would check in the data room. Teams remember the candidate who protected the file under mild pressure. They also remember the candidate who invented a figure to keep the conversation smooth. Invention is the one habit this seat cannot absorb.

After the analyst seat

The classic next seat in a bank is associate, often after a promotion or after a return from graduate business school. The work shifts. You still understand the model and the room, and you now direct analysts, talk more often with clients, and carry pieces of the process that used to arrive on your desk fully formed. Some people leave for corporate development and take the same instincts inside one company. Others move to investment roles, credit, or advisory boutiques where the team is smaller and the analyst title covers a wider set of tasks.

What travels is the reputation for a clean file. A future employer can test that reputation quickly. They ask about a process that got messy and what you personally kept true. They ask how you handed work to another analyst when you were away. They are listening for ownership without exaggeration. The published pay span, from $63,720 at entry to a high end of $239,700, is wide enough to cover many of these later seats in the broader occupation. Your own move up that span still depends on duties you can name, not on the calendar alone.

Compensation when the published span is wide

Begin by locating the offer, because the span is too wide for vibes. Near $63,720, you are looking at entry in the national picture. The step to the national median is $39,020, up to $102,740. Ask which staffing responsibilities mark that step in this firm: running a model with less review, owning the data room on a live process, or producing pages that go to a client meeting without a full rewrite. Bonus practices in this industry can be large and are not printed in these wage figures, so discuss salary with the figures you actually have, and discuss bonus as the firm's own plan rather than as a number you invent.

If the conversation leaps to $239,700, slow it down. That figure is the high end of the published range in South Dakota. It sits $136,960 above the national median, and it is a different statistic from New York's median of $127,930, from Oregon's $120,590, and from every other median in the set. A New York offer belongs next to $127,930, with the $25,190 gap above the national median as context, not next to a high end from another place. The $64,930 spread between the highest and lowest state medians is a warning against treating the country as one price.

Bring evidence that fits an analyst's real job. A model you maintained, a room you kept current, a contradiction you caught. Then say where the offer sits among $63,720, $102,740, and the high end you are careful not to mislabel. Geography gets its own sentence: name the state median if the workplace is one of the places listed, and keep South Dakota's high end in its own sentence so nobody blends them. Wide ranges reward people who can speak precisely. This occupation already pays you to do that with other people's numbers. Do it with your own.

The top of Mergers and Acquisitions Analyst pay — and how to get there with AI

$239,700what Mergers and Acquisitions Analyst pay reaches in South Dakota

Highest state-level top-of-range annual wage for Financial and Investment Analysts, 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 — Financial Managers — reaches $370,780 in New York.

$63,720entry$102,740middle$239,700top end

An analyst at the top of the mergers and acquisitions range owns a sector and a workstream deeply enough that a deal team cannot start without them, rather than being someone who can build any model reasonably well.

Preparing all materials for a transaction, performing securities valuation and pricing, and monitoring corporate and industrial developments are the standard duties, and everyone at your level already does them. Modelling and document tools have compressed the mechanical part further: comparables pulled and formatted, filings condensed, data rooms indexed. What stays scarce is judgement on something narrow, one sector's economics, one transaction type, one piece of diligence that others routinely get wrong, plus the nerve to defend it in front of people who lose money if you were careless. South Dakota pays this occupation more than any other state, though for most analysts the sector choice moves the number further than the address does.

Your playbook, by where you are now

Just startingBe flawless first, then be narrow

  1. Rebuild one transaction's valuation from the filings alone, without the team template, and reconcile every difference.
  2. Keep an error log in Microsoft Excel of your own mistakes and the check that would have caught each one.
  3. Read corporate and industry developments in one sector daily until you can predict what a management team will say.
  4. Have Claude reduce a long filing to questions you must verify, never to conclusions you repeat, and answer each in the document itself.

What proves it: A model senior people use without rechecking every cell.

Realistic span: the first two years

A few years inOwn a workstream

  1. Take the diligence workstream others avoid: quality of earnings, working capital, or contract review.
  2. Automate the repetitive pull with Alteryx or the business intelligence software your firm runs, so your hours go to analysis rather than formatting.
  3. Present your reports yourself instead of passing them upward, since valuation credibility is built in the room.
  4. Write the sector primer your team keeps reusing, and refresh it every quarter.
  5. Mentor junior team members deliberately, because teaching exposes what you only half understand.

What proves it: A sector primer plus a diligence workstream that is yours by default.

Realistic span: years three through five

ExperiencedBe the reason the deal team is hired

  1. Specialise to a transaction type, carve-outs, take-privates or cross-border deals, where few people can do the work at all.
  2. Build direct relationships with the corporate development teams who buy inside your sector.
  3. Take mandates needing an unusual valuation view, including green financial instruments and sustainability-linked structures where pricing is still argued over.
  4. Aim at the financial manager route once you would rather set the plan of action than execute it.

What proves it: Mandates arriving at your firm because of your name in one sector.

Realistic span: from year six

The next 90 days

Choose your sector this quarter and prove it in writing. Take one industry, read every filing, transcript and trade publication from the past four quarters, and write a primer explaining how those companies actually make money, what a buyer is really paying for, and which three numbers the valuation turns on. Then price two recent transactions in that industry yourself, from public information alone, and compare your figures against what was paid. Wherever you were wrong is the education. Circulate the primer to your deal team and keep it current, and within a year you become the person asked before a pitch rather than after the mandate lands.

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

Careers related to Mergers and Acquisitions 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 the work that eats your nights: financial data and diligence. Extracting financials from filings, building comparable sets, and combing a data room is where analyst hours vanish. Finance-grade tools — Daloopa for financial data, Hebbia for document analysis, Rogo as an AI analyst, AlphaSense for research — do this inside compliance controls. Learn the ones your firm has approved and let them clear the mechanical hours so you can check the output and actually think about the deal.

Never paste deal documents, target financials, or MNPI into public ChatGPT — that's a compliance breach with real consequences. Reserve consumer tools for general methodology and learning phrased with no confidential specifics, and verify every number AI produces against the primary source. The tools accelerate the grind; the modeling judgment and the deal thesis are what get you promoted.

The one rule, forever: Material non-public information and deal confidentiality are legal lines, not preferences. Never paste target financials, NDAs, data-room documents, board materials, or any MNPI into a consumer AI tool — use only firm-approved, enterprise tools inside information-barrier and compliance controls. Every AI-built model, comp, or diligence finding is a draft you verify against the source before it reaches an MD, a committee, or a client; the numbers and the recommendation are your responsibility and your liability.
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
Screen and source acquisition targets at scale
Why this pays: A better funnel of targets is the input to every deal, and the analyst who can build a sharp, criteria-driven screen becomes valuable to corporate development and private equity teams — exactly the buy-side roles that carry the top of the band. AI compresses days of screening into hours.
S&P Capital IQ ProPitchBookAlphaSense
1
Use Capital IQ Pro and PitchBook to run quantitative screens and AlphaSense to scan filings, transcripts, and news for qualitative signals — then verify every candidate against the source before it goes on a list.
2
Define rigorous screening criteria before you pull the universe.
Copy-paste this prompt
Act as a corporate development analyst building an acquisition screen. Our thesis: [a strategic buyer in industrial software wants bolt-on targets under $200M EV with recurring revenue]. List the screening criteria I should apply (financial thresholds, business-model markers, ownership/exit-readiness signals), the qualitative red and green flags to layer on, and how to rank the resulting list by strategic fit. General methodology only — I'll run the actual screen in approved tools.
Keep any live mandate or target names out of consumer tools. Verify every screened candidate's figures against filings before presenting.
What you'll haveA sharp, defensible target list built in hours — the sourcing skill that makes you valuable to the corporate development and PE teams where top pay sits.
2
Build and audit the deal model — accretion/dilution, LBO, DCF
Why this pays: The deal model is the analytical core of an M&A transaction, and a clean, defensible one is what earns senior trust. AI-assisted building and QA — flagging broken links, pressure-testing assumptions, checking the accretion math — lets you build faster and avoid the errors that embarrass analysts in front of a committee, the credibility that gets you promoted.
Microsoft Excel (Copilot)MacabacusRogo
1
Speed model construction and formatting with Macabacus and Excel Copilot, and use an approved AI analyst like Rogo to QA the logic — then verify every driver and output yourself.
2
Pressure-test an accretion/dilution or LBO model's structure and assumptions.
Copy-paste this prompt
Act as an M&A associate reviewing my work. Here is the structure and assumptions of an [accretion/dilution] model for a [stock-and-cash acquisition]: [describe structure and assumptions — no confidential figures]. Pressure-test it: which assumptions most drive EPS accretion, what synergy and financing assumptions a rigorous MD would challenge, the common modeling errors to check for in this deal type, and the sensitivity tables I should show. General methodology only.
Discuss structure and methodology, never confidential deal figures. You own every number and assumption — verify the model's logic yourself.
What you'll haveCleaner, faster, better-stress-tested deal models — the analytical credibility that earns senior trust and moves you toward associate.
3
Tear through the data room in hours, not weeks
Why this pays: Due diligence means reading thousands of pages under deadline, and missed red flags are real deal risk. AI document analysis surfaces the change-of-control clauses, customer concentration, and revenue-recognition issues far faster than manual review — the execution leverage that lets a lean deal team do more and makes seniors want you staffed on their transactions.
HebbiaV7 GoDatasite (AI)
1
Query the data room with a finance-grade tool like Hebbia or your VDR's AI (Datasite), and use V7 Go or a contract-analysis tool to extract key terms across hundreds of agreements — then verify each finding in the source document.
2
Set the diligence priorities and the specific red flags to hunt for.
Copy-paste this prompt
Act as an M&A diligence lead for a [buy-side acquisition] in [industry]. Give me the diligence request list and the specific red flags to search the data room for: change-of-control and assignment clauses, customer and supplier concentration, revenue-recognition and quality-of-earnings risks, pending litigation, related-party transactions, and off-balance-sheet items. Turn each into a precise question I can put to the documents. General framework only.
Only run real data-room documents through firm-approved tools inside the information barrier. Verify every AI-surfaced finding in the source — missed diligence is a liability.
What you'll haveFaster, deeper diligence with a lean team — the execution leverage that makes senior bankers and deal principals want you on their transactions.
4
Extract and normalize financials and quality-of-earnings
Why this pays: Accurate, normalized financials are the foundation of every valuation, and quality-of-earnings work — separating real, recurring earnings from one-offs — is where analysts add insight beyond the raw numbers. AI extraction plus your judgment on the adjustments is the combination that gets your analysis trusted.
DaloopaMicrosoft Excel (Copilot)ChatGPT
1
Use Daloopa to pull and structure historical financials from filings, then work the normalization and EBITDA adjustments in Excel — verifying every extracted figure against the source statement.
2
Build the quality-of-earnings adjustment framework before you touch the numbers.
Copy-paste this prompt
Act as a transaction services analyst. For a quality-of-earnings analysis on [a target in consumer products], list the common EBITDA adjustments to test for (one-time items, owner add-backs, run-rate normalizations, accounting-policy differences), the ones most often abused by sellers, and the supporting evidence I should demand for each. Give me a checklist to work through. General methodology only — no target data.
AI extraction speeds the pull but can misread a statement — reconcile every figure to the source, and treat every add-back skeptically. You own the normalized number.
What you'll haveAccurate, normalized financials with a defensible quality-of-earnings view — the analytical rigor that makes your valuation trusted by seniors and committees.
5
Draft the deal narrative — CIM, IC memo, and synergy case
Why this pays: The investment committee memo and the synergy thesis are where an analyst's judgment becomes visible to decision-makers. AI that drafts the structure and first-pass narrative — inside approved tools — frees your hours for the argument itself, and a sharp, well-argued memo is what gets an analyst noticed and advanced.
RogoMicrosoft PowerPoint (Copilot)Claude
1
Use approved AI to draft the memo structure, the market section, and the first-pass narrative, then sharpen the deal thesis and every number yourself — the argument and the accuracy are what matter.
2
Outline an investment committee memo and stress-test the deal thesis.
Copy-paste this prompt
Act as an M&A associate. Help me outline an investment committee memo for [a strategic acquisition] in [industry]. Propose the section flow (transaction overview, strategic rationale, valuation, synergies, diligence findings, risks, recommendation), the key message on each section, and the hardest questions a skeptical committee will ask about the synergy case and the price. General structure only — no confidential deal data.
Draft structure and generic narrative only; never input confidential deal or target data into a non-approved tool. Verify every figure before it reaches the committee.
What you'll haveA tightly argued memo and synergy case drafted fast — the visible judgment that gets an analyst noticed by the decision-makers who drive promotions.
6
Move up — and move to the buy-side (corp dev or private equity)
Why this pays: In M&A, the top of the band is a buy-side and seniority story: senior analyst, corporate development, or private equity, where pay reflects deal ownership and carry. Using AI to clear execution work builds the reputation and free hours to make that move — the single biggest lever on total comp.
ClaudePerplexity FinanceLinkedIn
1
Be the analyst who executes flawlessly and thinks like a principal — using AI to clear the mechanical work so your visible contribution is judgment and deal ownership, which is what gets you promoted or recruited to the buy-side.
2
Build a candid plan to reach the next level or move to corp dev or PE.
Copy-paste this prompt
Act as a finance career mentor. I'm an M&A analyst aiming to [make associate / move to corporate development / break into private equity]. Given my background: [summary], what deal experience and skills each path actually requires, how the work and compensation differ (base, bonus, carry), and how I should position and network for the move. Give me a candid 12-month plan with the milestones that matter.
The top of the band is driven by deal responsibility and buy-side carry, not a title alone — the plan is about reputation and relevant deal exposure.
What you'll haveA track record of flawless execution and a credible path to the buy-side — the seniority and carry that carry total comp toward $239,700.
Your 12-month sequence to the top of the range

How the plays above stack into a path from median pay toward the $239,700 tier.

Month 1
Learn your firm's approved AI tools for financial extraction, comps, and document analysis; verify everything against filings.
Months 2-3
Bring AI QA into your deal models — accretion/dilution, LBO, DCF — and catch errors before they reach review.
Months 3-6
Apply AI document analysis to a live data room; work through a full diligence and quality-of-earnings pass faster and deeper.
Months 6-9
Use approved AI to draft IC memo structure and the synergy narrative; redirect your hours to the deal thesis.
Months 9-12
Build sector fluency and a sharp target-screening capability with AI research tools; bring differentiated ideas to seniors.
Year 2
Execute flawlessly, target a senior, corporate development, or private equity seat — the buy-side move toward $239,700.
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 — professional standards and credentialing. Not leftover 94 CFP (that is financial-planner / financial-advisor) and not Level II or Level III.

Next steps for a Mergers and Acquisitions 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.

Mergers and Acquisitions 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.

Mergers and Acquisitions 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 Mergers and Acquisitions 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 Mergers and Acquisitions 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 Mergers and Acquisitions Analyst work, not a claim that they list a counted SOC 13-2051 inventory.

Build a Mergers and Acquisitions Analyst resume on Resume Now

Write a Mergers and Acquisitions 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 Mergers and Acquisitions Analyst resume on Zety

A Mergers and Acquisitions 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 Mergers and Acquisitions Analysts earn by state

These are the Bureau of Labor Statistics’ own figures for Financial and Investment Analysts, 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.

New York
$127,930
highest of them · +25% vs the national median
Puerto Rico
$63,000
lowest of the 44 states and territories that qualify · -39% vs the national median
The same job pays $64,930 more a year at the median in New York than in Puerto Rico — 103% 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, $239,700, is a different statistic in a different place: it is the 90th-percentile wage in South Dakota. The state that pays the typical worker most and the state where the best-paid go highest are not always the same one.
New York$127,930Oregon$120,590Massachusetts$111,040California$109,110New Jersey$108,610Washington$107,210District of Columbia$105,780Virginia$105,490

Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025, SOC 13-2051. 44 states and territories 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 M&A analysts?
No. AI can't own a deal thesis, negotiate terms, read a management team, or take responsibility for a recommendation to a committee. It's automating the grunt work — screening, extraction, formatting, first-pass diligence — which raises the bar: your value shifts to judgment, synergy analysis, and deal execution earlier than before. Analysts who lean into that advance faster.
Is it safe to use AI in M&A given confidentiality and MNPI?
Only with firm-approved, enterprise tools inside information-barrier and compliance controls. Never put target financials, NDAs, data-room documents, or MNPI into consumer tools — that's a serious legal and compliance breach. And verify every AI output against the source, because you own the numbers and the recommendation.
Which AI tools are actually used in M&A?
Finance-grade platforms: Daloopa for financial data extraction, Hebbia and AlphaSense for document analysis and research, Rogo as an AI analyst, Capital IQ Pro and PitchBook for screening, plus Excel and PowerPoint Copilot and Macabacus for modeling and materials. Many firms also deploy internal assistants. Use whatever yours has approved — never consumer tools on deal data.
How does AI actually raise an M&A analyst's pay?
Indirectly but powerfully. Pay at the top is driven by seniority and the buy-side, so AI's payoff is clearing the execution grind to free your hours for the modeling judgment, diligence insight, and deal ownership that get you promoted to associate or recruited into corporate development or private equity — where the band tops out.
Do I still need to know how to model if AI can do it?
Absolutely — more than ever. AI drafts and checks, but you have to understand every driver to defend the model to an MD or a committee and to catch the error AI introduces. The analysts who thrive use AI to go faster on modeling they fully understand, not to skip learning it. The judgment is the job.
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