◆ Statistics

What a quantitative researcher
really does.

20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.

20evidenced tasks
132,130in the US (2025)
$81,100median pay / year
8systems it runs on
See the 20 tasks ↓Open in the atlasThe full career map →
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Provide recommendations on financial matters
Summarise the fund-level and parent company financials, highlight thre…3 sources agree

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The work, task by task

20 tasks
Hands on the work14
Provide recommendations on financial matters+
Summarise the fund-level and parent company financials, highlight three material risks to cash flow and two recommended actions on hedging, capital allocation or dividend policy, with numbers and a cover memo for the CIO by Thursday.
escojdonet3 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Assist in developing trading algorithms and risk tools+
Back-test the proposed alpha signal against the last two years of tick and daily fills, calculate P&L, Sharpe and drawdown, surface the parameters that dominate risk, and produce a short note for the quant PM before the desk meeting on Wednesday.
jdonet2 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Provide analytical support to researchers or traders+
Deliver cleaned factor exposures, attribution tables and a one-page summary of signal performance with caveats and any data gaps that could bias estimates to the research lead by end of day Friday.
jdonet2 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Define or recommend model specifications or data collection methods+
Recommend the data fields, sampling frequency and overlap adjustments for the new macro factor, describe expected biases and an ETL checklist, and send the proposal to the data engineer and head of research by Tuesday noon.
jdonet2 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Perform stress tests and scenario analysis+
Run stress tests and scenario analysis on the credit portfolio using last quarter's loan-level data, apply the severe, adverse, and baseline macro paths through next three years, flag accounts breaching the 99th percentile loss and produce a one-page executive summary for Friday.
jd
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Interpret financial statements+
Interpret the latest consolidated financial statements for client Horizon Bank, reconcile off-balance items and loan provisions to cash flows, identify three ratio anomalies that change credit grade, and write a concise note with recommended covenant actions for Monday morning.
esco
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Offer financial services+
Design a compliant packaged financial service for small commercial clients that includes a revolving credit line, FX hedge option, and fee schedule, model pricing assumptions over five years, and prepare client-facing one-page term sheet for the relationship manager by Thursday.
esco
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Prepare financial projections+
Prepare five-year financial projections for the retail mortgage book using current origination rates, prepayment assumptions and stress default curves, show central and downside cases, and deliver a forecast spreadsheet with clear assumptions tab by Tuesday.
esco
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Grow the practice3
Watch and assess3

What the work runs on

named inside the evidenced tasks
16 tasksMicrosoft Excelcompile statements, run scenario math and produce concise tables for recommendationsOpen its task library →
5 tasksMicrosoft Power BIvisualize signal performance and flag data gaps for the research lead if needed
4 tasksMicrosoft Officedraft the cover memo and format the recommendation for the CIO
3 tasksIBM SPSS Statisticsanalyses time series and cross-sectional macro data and tests statistical significance of risk factors
2 tasksC++run efficient back-tests and compute performance and risk statistics on high-frequency and daily data
2 tasksLinuxexecute compute jobs and manage results files for the back-tests
1 taskMicrosoft Azureif cloud compute or storage design is required, outline where datasets and scheduled jobs should live
1 taskC#implements complex statistical algorithms and model backtesting pipelines with performance and integration to trading systems
Browse every evidenced software task →

The same task, four heights

this page is height one
ExecuteDo today's task, with fewer mistakesyou are here → ImproveMake it easy for the next person to acceptin the atlas → DecideWork out the right move when it is unclearin the atlas → BecomeLearn the pattern so it stops coming backin the atlas →

Can AI actually do this job?

the honest answer

It can

where it genuinely helps
  • Explain the theory behind the work
  • Draft, tidy and structure your writing
  • Rehearse a hard conversation before you have it
  • Build a study plan that fits your gaps

It cannot

where it stops, completely
  • Be in the room where a quantitative researcher actually works
  • Carry the responsibility when the call is wrong — that weight stays yours
  • Notice what no one wrote down: the hesitation, the thing left unsaid
  • Live with the outcome

What the work pays

two countries, two different measures

United States

this exact occupation · BLS 2025
  • $81,100 a year — the middle: half earn more, half earn less
  • The lowest tenth earn near $48,460; the top tenth near $151,490
  • 132,130 people employed in this occupation

India

the occupation GROUP, not this job · PLFS via ILOSTAT 2025
  • ₹38,298 a month — the median for Professionals, the group this work sits in
  • India publishes pay by broad occupation group, so this covers many jobs besides this one. It is a shape, not a salary.
read this carefullyThese two numbers are not comparable and must not be converted into each other. One is a yearly figure for this job alone; the other is a monthly figure for a whole family of jobs. What travels between them is the pattern, not the amount: experience lifts pay almost everywhere.

Where the evidence lives

open any of it yourself
O*NETThe US Department of Labor's own record of this job9 of these tasks ESCOThe European skills and occupations register9 of these tasks Job descriptionsReal postings, in the wild8 of these tasks US Bureau of Labor StatisticsPay and employment, by occupation2025 figures UK NOS FSPISM17Provide cash and currencies research and analysis support for portfolinational standard UK NOS FSPISM16Provide research and analysis of alternative investments support for pnational standard

Close to this work

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Questions people actually ask

You spend most of the day coding, testing models, and reading data. Morning: check overnight market moves, run risk reports, and discuss priorities with traders or researchers. Afternoon: build or refine financial models in C++ or Python, run stress tests and scenario analysis, and meet to review results.

Evening: update metrics dashboards in Power BI or Excel, commit code on Linux servers, and plan datasets or experiments for the next day. Times vary with markets — more urgent near market open/close or earnings and macro news.

Expect C++ and C# for high-performance pricing or execution code, plus Linux for servers and deployment. Excel and Power BI are used for quick analysis, reports, and dashboards for traders or managers.

You may use Microsoft Azure for data storage and notebooks, and IBM SPSS for some statistical work. The exact stack depends on the firm; mention these systems on your resume if you’ve used them.

Use AI as a tool for signal discovery, feature engineering, or risk classification, but always back tests with out-of-sample and stress scenarios. Document assumptions, data sources, and version your models so you can reproduce results.

Avoid opaque “black box” models for trading decisions unless you add interpretability checks, limits, and real-time monitoring. Pair ML outputs with traditional models and human oversight before deployment.

The U.S. Bureau of Labor Statistics reports 132,130 employed under this SOC. The median wage is $81,100 per year; the lowest tenth is $48,460, and the top tenth is $151,490 per year (BLS).

Compensation often varies by industry, location, and experience; firms may add bonuses or equity on top of base salary.

Learn probability, statistics, linear algebra, and numerical methods. Practice coding in C++ and C# for speed and Python for prototyping. Get comfortable with Excel and Power BI for reporting and quick checks.

Build concrete projects: a pricing model, backtest a trading strategy with real historical data, and a stress-test suite. Put code on GitHub and show full workflow: data ingestion, model, backtest, and dashboard.

A quant researcher focuses on building pricing models, risk tools, and trading algorithms using advanced statistics and finance knowledge. They run stress tests, interpret financial statements, and track trading system metrics.

Data scientists might work across nonfinancial domains and focus more on product metrics or customer data. Traders make execution decisions and use quant outputs; quants supply the models and analytical support that traders rely on.

Programming skill in a compiled language like C++ plus the ability to write correct, fast numerical code. Firms need people who can implement models that run in production on Linux.

Combine that with solid probability/statistics and an ability to explain model limits to traders or managers. If you can code a tested pricing model and show backtest results, you stand out.