How a derivatives trader turns controls into mandate
$386,910estimated top of the range · middle $120,000 / yr
AI is transforming this role
Derivatives Traders in the United States earn a median of $120,000 a year. Pay starts near $65,000. The top of the range is estimated at $386,910. 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
$65,000
Top-end estimate
$386,910
Education
Bachelor's degree in Finance or Math
Wages — PayCrunch estimate. The Bureau of Labor Statistics does not publish a separate wage series for Derivatives Trader; 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 Derivatives TraderReviewed September 2026
We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for Derivatives Trader work right now.
NumericNEWPaid / see site
AI-driven month-end close, reconciliation, and reporting.
How a Derivatives Trader uses it: automate reconciliations and close the books faster
HebbiaNEWEnterprise / see site
AI that reads and analyzes large financial documents and filings.
How a Derivatives Trader 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 Derivatives Trader 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 Derivatives Trader 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 Derivatives Trader 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 Derivatives Trader 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 Derivatives Trader 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 Derivatives Trader 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 Derivatives Trader uses it: analyze big reports or spreadsheets and turn messy notes into clean, finished writing
A desk that already has a risk sheet
I staff a derivatives desk, and the morning that tells me who belongs there starts before the economic calendar gets noisy. Overnight notes from another office are already in the folder. A risk manager has a sheet of limits. Compliance has a recorded-line review on the calendar. The person I want in the junior seat has read those notes, knows which client calls are already booked, and can say what the desk is responsible for today in plain language. The tools are screens, phone lines the firm records, and a paper trail a supervisor can reconstruct next month. This is a job inside a firm that already has a compliance program. A personal brokerage login is a different life.
The day splits into kinds of work that share a row of monitors and still hire differently. One seat faces clients of a bank or a fund and explains products the desk is allowed to offer. Another seat watches the positions the firm holds, inside limits written by someone else. A seat at a futures commission merchant sits closer to customer orders in listed futures and to the operational record those orders need. I will not describe how to price an option, how to hedge, or how to build a trading plan. Those choices belong to the firm that employs you, under its own risk rules. What I can describe is the career: who hires, which registrations open which seats, and how pay conversations go when the only honest figures are estimates.
People who last on these desks are calm when a number moves and boringly clear when they write. You will speak to sales colleagues, to risk, to operations, and sometimes to a client who is angry about a fill. You will hand a position to another time zone with a note the next person can trust. You will sit in a meeting where someone asks why yesterday's result looks the way it looks, and you will answer from the record, not from a story you invent on the way upstairs. If that kind of day sounds dull, this career will feel dull. The drama in films is a poor guide to the actual seat.
Four kinds of employer, four kinds of seat
Banks hire derivatives traders onto desks that serve the bank's clients and onto desks that hold risk for the bank itself. The products have familiar names: options, futures, swaps, and packages built from those. Rates, equity, credit, foreign exchange, and commodities can each be a separate desk with its own head, its own juniors, and its own compliance checklist. A new hire rarely touches all of them. You join one desk, learn its products at the level the firm teaches, and earn a wider view only after people trust your record.
Hedge funds hire a smaller number of seats, often after you have already worked somewhere that taught you the products. The fund's style, its investors, and its risk committee define the job more than a generic title does. Proprietary trading firms hire people to trade the firm's own capital. The culture can be flatter, the feedback faster, and the registration picture different from a broker-dealer, which is why you ask compliance before you assume a licence from the last job still fits. Futures commission merchants hire people around customer futures business: the orders, the accounts, and the registrations that futures work requires. If a posting says trader and the firm is an FCM, read the seat description twice. The word covers more than one craft.
Geography matters in a career sense, not as a wage table. Large desks cluster where the firms already have trading floors and compliance staff. Some seats are in a headquarters city. Some are in a regional office that covers a set of clients. A few are attached to a smaller shop where one person wears three hats and still has to keep the same kind of records. When you compare offers, compare the employer type first. A bank program, a fund, a proprietary firm, and an FCM can use the same job title and mean four different Tuesdays.
Registrations that unlock a specific seat
Some seats require a registration before you can do the work. Treat these as registrations, granted and supervised by a regulator, not as a school certificate you frame and forget. At a broker-dealer, a common requirement is the Series 7 registration, associated with the Financial Industry Regulatory Authority. FINRA is the body people mean when they talk about that registration for a general securities seat. The Series 7 is tied to representing a broker-dealer. It is the registration for that kind of seat, and it is not something you hold in the abstract with no firm.
Futures work points at a different registration. The Series 3 registration is the one firms and candidates talk about for futures, and it sits with the National Futures Association. If the seat is at an FCM or otherwise in listed futures, ask whether Series 3 is the registration that seat requires, and ask the firm to sponsor or to tell you the path it actually uses. Do not collect registrations the way some people collect certificates. Each one belongs to a kind of business.
Some trader seats require the Series 57 registration, again through FINRA, for people who are traders in the sense that registration covers. A desk head who says you need Series 57 is talking about that seat's regulatory status. A desk head who says you need Series 7 is talking about a broker-dealer role. A desk head who says Series 3 is talking about futures. You can need one of these, or a combination, depending on what the firm is allowed to do and what your name will be attached to. The person who knows is the firm's compliance officer, not a stranger on a forum.
I do not coach the content of any registration, and I do not quote scores, clocks, or fees. Those details live with the granting body and they change. What I need in an interview is honesty about where you stand: already registered, sponsored and scheduled, or not yet in the process. Read the official pages rather than a summary. FINRA's site is finra.org. The National Futures Association's site is nfa.futures.org. If a recruiter promises a registration the firm cannot sponsor, believe the compliance manual, not the recruiter.
Which registration belongs to which seat
Series 7 is a FINRA registration used at a broker-dealer. Series 3 is the futures registration associated with the NFA. Series 57 is a FINRA registration some trader seats require. The firm's compliance officer names the one your offer needs.
How a junior seat is actually filled
Campus programs still feed the large banks. The path that works is an internship on a markets desk, a summer where someone lets you own a small recurring task, and a full-time offer that names the desk. Degrees I see most often are finance, economics, mathematics, engineering, and related fields. The degree is not a registration. It is a way of showing you can learn a technical job. A graduate who can explain a simple product clearly, who has kept a flawless record of a small responsibility, and who treats compliance as part of the craft will beat a graduate who only talks about wanting to be on a desk.
Experienced hiring is narrower. Funds and proprietary firms often want a track record inside a firm, which means references from a desk head or a risk manager who actually saw your work. Bring a description of the products you sat with, the employer type, and the registration you hold. Leave out any claim about a secret method. I end those interviews early. Operations and middle-office people sometimes move toward a front-office seat after years of clean work. That move is real, and it is slower than a slogan. If that is your plan, learn the products your firm already trades, keep your registrations current for the seat you want, and ask for a project a trader will sign their name next to.
In the interview I ask what you did on a specific week, who reviewed it, and what you wrote down when something looked wrong. I ask which registration the seat you want requires, and whether you have started it. I ask how you behave when a senior person is impatient. I do not ask you to pitch a trade. You should ask us which desk, which employer type, who sets limits, how juniors are taught, and what the first year actually contains. A famous firm with no training and a fuzzy registration plan is a worse first job than a plainer firm that will sponsor the right registration and let you learn one product properly.
Junior, trader, desk head
The early years are apprenticeship under a louder name. You reconcile, you prepare notes, you listen to client calls, you learn the firm's systems, and you take tasks that are small until you miss one. People who do those tasks carefully get larger ones. People who treat them as beneath the title stay junior. A trader's title, when it is real, means the firm lets you act inside a limit and expects you to explain the result. A desk head runs staffing, the relationship with risk and compliance, and the quality of the juniors. Some excellent traders never want that office. Say so. A career can stay close to the products without becoming management.
Laterals happen when a desk needs a product you already know. Moving from a bank to a fund, or from an FCM toward a different futures seat, means re-checking registrations before you resign. A Series 7 tied to a broker-dealer does not automatically follow you into a firm that is not a broker-dealer. A Series 3 does not substitute for a FINRA registration a new seat requires. Build the habit of asking compliance at the new firm, in writing, what must be active on your start date. Gaps in that paperwork have delayed start dates more often than gaps in talent.
There is also a path out that still uses the same early training. Risk management, product control, and compliance hire people who have sat on a desk and can read the record. Those moves are not a failure. They are how some of the calmest careers in this industry are built. If you want to stay in the trading seat, protect your reputation for accurate notes and for telling a risk manager bad news early. That reputation is the only portable asset I trust when a name comes up in a hiring meeting.
Estimated pay, and how to use it without a map of states
The Bureau of Labor Statistics does not publish a separate wage series for this exact title, so the figures here are PayCrunch estimates rather than a published wage series for derivatives traders. Use them as anchors for a conversation, and do not pretend they are a government table for this job. The estimated entry level is $65,000. The estimated median is $120,000. The gap between those two is $55,000. That gap is the practical distance from a first full-time seat to the middle of this estimate. A junior program that starts near $65,000 and describes a path toward the median is talking about a real step. A posting that advertises the median for a seat with no book, no registration, and no training is borrowing a number it has not earned.
The estimated top is $386,910. The distance from the median up to that estimated top is $266,910. I would not open a junior negotiation anywhere near $386,910. That figure belongs, if it belongs anywhere in your own case, to a later seat with responsibility the estimate is trying to reflect. Pay in this career often mixes a base with a bonus the firm decides after the year. I will not invent a split, because no split is in these figures. Ask the offer to show base and any variable pay as separate lines, then compare the base to $65,000 and to $120,000 before you let a hypothetical year-end number do all the talking.
There is no state median to quote, and none of these dollars should be pinned to a state. Firms in the same city pay different seats differently, and an estimate cannot referee that. What you can say in a conversation is simple. If the base is under $65,000, ask what the seat actually is and when the wage moves. If the base is near $120,000, you are near the middle of the estimate, and the rest of the talk is the registration, the desk, the bonus plan in writing, and the hours the desk really works. If someone waves $386,910 at a first-year hire, ask which responsibility in the offer matches a top-of-estimate seat. Keep the registrations named correctly. Series 7, Series 3, and Series 57 are reasons a firm can put you in a seat. They are not a substitute for reading the offer.
Before you accept, write three lines on one page: the employer type, the registration the compliance officer confirmed, and the base next to $65,000 and $120,000. Add the estimated top only if you are looking at a senior seat and you can say why. Leave tactics out of the salary talk the same way you leave them out of a first interview. The firm will teach you its products inside its limits. Your job in the negotiation is to know which number is entry, which number is the middle, and which number is a distant estimate you have not yet been offered.
The top of Derivatives Trader pay — and how to get there with AI
$386,910top-end estimate for Derivatives Trader
PayCrunch estimate - derived from the closest occupation BLS tracks (Securities, Commodities, and Financial Services Sales Agents, 41-3031). This figure is PayCrunch’s estimate, not a Bureau of Labor Statistics published wage for this exact title.
And the role it leads to — Personal Financial Advisors — reaches $459,050 in Oregon.
$65,000entry$120,000middle$386,910top end
What separates a derivatives trader at the top of the range from one mid-range is often not the position taken but the ability to prove, line by line, that the tickets, the marks and the client records behind it are right.
Completing sales order tickets, keeping accurate records of transactions, supplying the latest price quotes, preparing financial reports that monitor client finances — most desks treat these as the part of the day to survive. A break found after settlement costs more than the trade earned. Someone who builds a check that catches the wrong ticket before the confirm lands, and who can show the count of what it caught, is making an argument no volume figure makes. Assistants that write code make that check a weekend project instead of a technology request that waits a year.
Your playbook, by where you are now
Just startingReconcile before you forecast
Rebuild the day's order tickets against confirms in Microsoft Excel each evening and log every break with its cause.
Learn enough Microsoft Visual Basic, with Cursor or GitHub Copilot beside you, to automate that comparison rather than eyeballing it.
Note which source produced each price quote you supplied, and how stale that source was when you used it.
Shadow client interviews covering assets, liabilities, cash flow, insurance coverage and tax status until you can document one an auditor would accept.
What proves it: A break log covering a full quarter, grouped by cause, with the fixes you made beside it.
Realistic span: your first two years on a desk
A few years inMake the desk's records measurable
Move the transaction record out of spreadsheets into Microsoft Access or FileMaker Pro so positions, tickets and clients join properly.
Publish a monthly quality sheet: breaks per thousand tickets, stale marks corrected, client reports filed late.
Test your own valuations against an independent calculation — AnalyzerXL, or a small pricing routine in C++ on Linux — and record every disagreement.
Standardise how financial options are explained to clients in writing, so suitability is evidenced rather than recalled.
Pull your own client positions from CSI Complex Systems ClientTrade instead of asking operations to send them.
What proves it: A desk quality sheet with a trend that operations and compliance both cite.
Realistic span: years three to seven
ExperiencedOwn the control, then ask for the book
Write the desk procedure for pricing, ticket review and mark verification, and get it approved as the standard.
Train two juniors to run the reconciliation and the client interview to the same documented level.
Bring the error record rather than a good month when you ask for a wider mandate or a larger limit.
If the client relationships interest you more than the tape, personal financial planning rewards the same discipline, and New York pays this occupation best either way.
What proves it: An approved desk procedure plus a documented widening of your mandate.
Realistic span: eight years and after
The next 90 days
For ninety days, reconcile your own tickets every evening and log every break. Match what you completed against the confirms and the position record, write each discrepancy down with its cause — wrong counterparty, wrong quantity, stale price, missed allocation — and how long it took to clear. Do not delegate it and do not skip a day. At the end you hold a count and a cause breakdown nobody else on the desk has, including whoever signs off your risk limit. Take the largest cause and fix it properly, with a check that runs by itself. Then state what it catches. That is a far stronger claim than a good quarter, and it still holds in a year when the market runs against you.
Wage figures: PayCrunch estimate. 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).
Your primary screen is still the Bloomberg Terminal or LSEG Workspace. Start by using their built-in AI - document and earnings summaries, natural-language search - to compress the reading you already do. Then open Python with the QuantLib library and GitHub Copilot: pricing, scenario, and backtest code that used to take a day now takes an hour, and that speed compounds across every trade.
For research, code help, and structuring your thinking, use Claude or ChatGPT, and Perplexity for public market context with citations - never for anything confidential or non-public. Keep positions, client flow, and proprietary strategy inside your firm's approved, surveilled systems; general AI is for public information and general methods only.
The one rule, forever: Trading is a regulated, surveilled activity - never act on material non-public information, and never paste confidential order flow, client data, position details, or proprietary strategy into a consumer AI tool. AI output is a hypothesis, not a signal: verify every price, Greek, and number independently, and you alone own the risk on any capital you deploy. Model risk is real - an unvalidated AI model can lose money fast.
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
Parse catalysts faster than the desk next to you
Why this pays: Event-driven and volatility trades are won by whoever digests a catalyst first and most completely. AI that reads an earnings call, filing, or central-bank statement in seconds lets you position ahead of the slow money - the timing edge that shows up directly in P&L.
AlphaSenseBloomberg TerminalPerplexity
1
Use AlphaSense or Bloomberg's AI summaries to pull the signal out of earnings transcripts, filings, and broker research the moment they hit - guidance changes, tone shifts, buried risk factors.
2
Turn the raw text into a trade-relevant read.
Copy-paste this prompt
Summarize what changed in this earnings call transcript versus the prior quarter for a derivatives trader: guidance revisions, margin commentary, capital-return changes, and any language that would move implied volatility. List the three most trade-relevant points. [Paste public transcript text only.]
Public information only, never non-public data. The summary is a starting read; verify the actual figures on your terminal before trading.
3
Pre-build watchlists and volatility screens so the moment a catalyst confirms your read, the structure is ready to execute.
What you'll haveFaster, more complete reaction to catalysts - the timing and information edge that turns into event-driven P&L.
2
Price and hedge sharper with AI-assisted quant code
Why this pays: Better pricing and hedging is a direct cost saving on every trade, and a validated systematic overlay adds an uncorrelated P&L stream. AI that helps you build and backtest models in QuantLib turns quant work from a bottleneck into an everyday tool.
Python (QuantLib)GitHub CopilotQuantConnect
1
Use GitHub Copilot with QuantLib to build and check pricers - vol surfaces, Greeks, exotic payoffs - far faster than by hand, then reconcile every output against your terminal and known benchmarks.
2
Prototype and backtest a systematic overlay before risking capital.
Copy-paste this prompt
Act as a quant developer. Write Python using QuantLib to build a delta-hedged short-straddle backtest on SPX options: define entry/exit rules, transaction costs, and daily re-hedging, and report P&L, max drawdown, and Sharpe. Explain every assumption I must validate. Use public or sample data only.
A backtest is a hypothesis, not a strategy - validate assumptions, stress it out-of-sample, and never deploy capital on unvalidated code.
3
Keep pricers and backtests in version control so your models are reproducible and auditable when risk or compliance asks.
What you'll haveSharper pricing and hedging plus validated systematic overlays - lower costs and new P&L streams, at a speed manual quant work can't match.
3
Automate your risk and Greeks monitoring
Why this pays: Bonus tracks risk-adjusted P&L, and bigger limits go to traders who manage risk tightly. Automating your Greeks, scenario, and pre-trade risk views means you catch a dangerous exposure before it becomes a loss - the discipline that grows your book.
Build a live risk dashboard in Python or Excel with Copilot that rolls up your net delta, gamma, vega, and theta and flags when any breaches your limits.
2
Script the scenario shocks you care about - big moves, vol spikes, term-structure shifts - so you see the tail before you put on the trade.
3
Automate a pre-trade checklist that recomputes portfolio risk with the new position included, so nothing gets sized on intuition alone.
What you'll haveTighter, automated risk management - fewer surprises, better risk-adjusted returns, and the track record that earns bigger limits.
4
Structure better trades from a thesis
Why this pays: Two traders with the same view make very different money depending on how they express it. AI that helps you compare structures, strikes, and expiries lets you capture more of your view per unit of risk and cost - the difference between a good idea and a good trade.
ClaudePython (QuantLib)OptionMetrics
1
Describe your market view and let AI lay out the expression choices to pressure-test your own.
Copy-paste this prompt
I have a view that 30-day implied vol on a name is too high into earnings but I expect a large move. Compare ways to express this with options - straddle, strangle, calendar, ratio, iron condor - with the payoff, main risks, and what has to be true for each to win. General options theory, no recommendation, no confidential data.
Use to broaden your thinking, not to pick the trade for you. Verify every payoff and Greek in QuantLib or on your terminal; the risk decision is yours.
2
Model the shortlisted structures in QuantLib with real vol-surface data so you compare risk-adjusted payoffs, not just intuition.
3
Size the winner against your risk limits and your conviction - structure and sizing are where edge is captured or lost.
What you'll haveTrades that express your view with better risk-reward - more P&L captured per idea, the core of a top-of-range book.
5
Compound skill with AI-driven post-trade review
Why this pays: Discretionary traders improve by learning from their own P&L attribution - which reads worked, where sizing hurt, which biases repeat. AI that structures that review turns every trade into training data, steadily lifting hit-rate and sizing discipline over a career.
ClaudePython (pandas)Excel
1
Keep a structured trade journal - thesis, structure, sizing, outcome - and use Python to compute your own P&L attribution and hit-rate by strategy and market regime.
2
Have AI find the pattern in your own results.
Copy-paste this prompt
Here is my anonymized trade journal with entry rationale, structure, size, and P&L: [paste de-identified summary]. Analyze it as a trading coach: where is my edge real, where am I losing money, what sizing or timing mistakes repeat, and what two changes would most improve risk-adjusted returns?
Use de-identified data only. Treat the analysis as a prompt for reflection, not gospel - you know the market context the data doesn't capture.
3
Turn the top recurring mistake into a written rule and track whether it improves next month - deliberate practice, not just screen time.
What you'll haveA compounding feedback loop on your own P&L - the steady improvement in hit-rate and sizing that separates durable top-of-range traders from lucky ones.
6
Become the desk's quant-literate trader
Why this pays: The trader fluent in both the market and the tooling gets more flow, bigger risk, and the promotion. Being the person who builds the desk's models, automations, and post-mortems makes you indispensable and expands your book.
PythonClaudeGitHub Copilot
1
Automate the desk's repetitive work - morning risk reports, marking, P&L explains - with Python and Copilot, freeing the whole desk to trade.
2
Write clear desk notes and trade rationales fast with Claude so your ideas travel to sales, risk, and portfolio managers - visibility is how flow and limits grow.
3
Own one piece of desk infrastructure - a pricer, a vol monitor, a backtest library - that others rely on; technical leverage is a direct path to a bigger seat.
What you'll haveMore flow, more influence, and a bigger book - the desk leadership that lifts total comp into the top of the range.
Your 12-month sequence to the top of the range
How the plays above stack into a path from median pay toward the $250,000 tier.
Month 1
Turn on your terminal's AI summaries and set up Python with QuantLib and Copilot. Rebuild one pricing or risk task as reproducible code and reconcile it to the terminal.
Months 2-3
Automate your Greeks and scenario dashboard; add an AI catalyst-parsing workflow (AlphaSense or Bloomberg) to your morning routine.
Months 3-6
Prototype and rigorously backtest one systematic overlay in QuantLib; start a structured, AI-analyzed trade journal.
Months 6-12
Own a piece of desk infrastructure and use AI post-trade review to sharpen sizing and hit-rate - the track record that wins bigger limits and bonus.
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 / quantitative-analyst. This page names Python (pandas) as a play tool on the live risk-dashboard and trade-journal plays. Not leftover 94 CFP and not CFA Level I as the lead (that is financial-analyst / credit-analyst).
Next steps for a Derivatives Trader
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.
Derivatives Trader work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Securities, Commodities, and Financial Services Sales Agents (SOC 41-3031). O*NET Job Zone 4 is typical: a bachelor's degree, so the honest next credential is a professional certificate or bachelor's-level coursework — not a random catalog dump.
The occupation's listed knowledge areas include Economics and Accounting and Sales and Marketing; the links search those subjects, not a generic 'career courses' list.
Derivatives Traders in this dataset list C++ among the tools in use, so a program that names that stack is a better fit than a survey course.
Coursera search for digital marketing and sales — a professional certificate or bachelor's-level coursework that lines up with sales, 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 Derivatives Trader work, not a claim that they list a counted SOC 41-3031 inventory.
Write a Derivatives Trader resume, or one aimed at Personal Financial Advisors, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.
A Derivatives Trader resume that names the actual tasks on this page, or the step-up title Personal Financial Advisors, beats a blank template when you apply.
What Derivatives Traders 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 $65,000, the median is $120,000, and the top of the range is $386,910. Those national figures are a PayCrunch estimate, not a Bureau of Labor Statistics published wage for this exact title.
It will replace traders who only push buttons and repeat a manual routine - and much execution is already automated. What it cannot do is own risk, read an ambiguous market, or answer to the P&L. Discretionary judgment about when the model is wrong, how much to size, and when to cut is still human. Traders who use AI to research faster and manage risk tighter take share from those who don't; the middle gets automated.
Is it safe to use ChatGPT or Claude for trading?
Only with public information and general methods - never with anything material and non-public, confidential order flow, client data, live positions, or proprietary strategy, which belong in your firm's surveilled systems. And treat every AI output as a hypothesis: verify prices, Greeks, and figures independently before a dollar of risk goes on.
Can AI find me alpha?
It can help you find and test ideas faster, but it does not hand you edge - if a signal were sitting in a public model, it would already be arbitraged away. AI's real value is speed and coverage: parsing catalysts, building pricers, backtesting, and reviewing your own trades. The edge still comes from your view, your risk management, and your discipline.
How does AI actually increase a trader's pay?
Through P&L. Faster catalyst reading gets you positioned earlier; better structuring captures more of your view per unit of risk; tighter automated risk management earns bigger limits; and AI post-trade review compounds your hit-rate. Bonus tracks risk-adjusted P&L, so every one of those is a lever on comp.
Which AI skill should a trader build first?
AI-assisted Python with QuantLib. It turns pricing, scenario analysis, and backtesting from slow, error-prone manual work into everyday tools, and it underpins everything else - risk dashboards, systematic overlays, and post-trade analytics. Fluency there is the highest-leverage skill on a modern desk.
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.