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ISSUE 001SUMMER 2026

QF-4QUANTITATIVE FINANCE CHAPTER 5 OF 10REVIEWED 2026-07-31

Quant roles: researcher, trader, developer, and data

Know the work product, review standard, and handoffs for each role.

Titles vary; the recurring output is the reliable guide.

WHAT THIS CHAPTER TEACHES

  • Researchers develop and test hypotheses, signals, forecasts, portfolios, and diagnostics.
  • Traders apply models and judgment to live markets, execution, inventory, and risk.
  • Developers build research, data, execution, and risk systems under correctness, latency, reliability, and recovery requirements.
  • Data specialists acquire, validate, version, and serve data; timestamp or entity errors can invalidate research.
  • Strong teams make assumptions explicit and share feedback between research and live behavior.

Quantitative researcher

Researchers formulate questions, build datasets, design models, validate results, and recommend deployment or rejection. Work can include forecasting returns, pricing, portfolio construction, execution, risk, or alternative data. The research note should document hypothesis, data, method, benchmark, result, limitation, and production implication.

Quantitative trader

Traders make or supervise live decisions involving pricing, execution, inventory, and risk. Some roles are highly automated; others combine models with judgment. Traders investigate unexpected P&L, market behavior, fills, and model responses. They often work closely with researchers and engineers.

Quant developer and software engineer

Developers build market-data, order, risk, research, simulation, and production systems. The priorities can include correctness, latency, throughput, reliability, observability, and recovery. A small bug can create financial loss, so testing and controls are part of the investment process.

Research engineer

Research engineers bridge exploratory work and scalable systems. They build data and experiment platforms, distributed computation, feature stores, backtest frameworks, and tooling that lets researchers work reproducibly.

Data scientist and data engineer

Data scientists model complex datasets and evaluate their economic usefulness. Data engineers acquire, clean, version, and serve data with lineage and monitoring. Entity matching, timestamp integrity, corporate actions, and vendor changes are central challenges.

Portfolio researcher and risk quant

Portfolio researchers combine forecasts, covariance, constraints, and costs. Risk quants model exposure, stress, liquidity, derivatives, or capital. They must understand estimation error and how relationships behave in extremes.

Derivatives quant

Derivatives quants develop pricing, calibration, hedging, and numerical methods for options and structured products. Roles can sit in banks, hedge funds, market makers, or software and risk teams.

Collaboration and handoff

A production handoff should specify model version, data, dependencies, expected behavior, limits, monitoring, fallback, and owner. Researchers explain assumptions; engineers challenge implementability; traders provide feedback from live markets.

Role overlap

Smaller firms may combine roles. A trader may code, a researcher may deploy, and an engineer may participate in strategy design. Larger organizations may specialize. Candidates should ask who owns the full lifecycle and how responsibility grows.

CURRENT AS OF 2026-07-31

Current Jane Street, Citadel, Two Sigma, and Bridgewater materials describe overlapping research, trading, data, engineering, and investment-implementation roles. Titles remain less reliable than recurring work and ownership.

SOURCES

  1. 01Jane Street: Interviewing
  2. 02Jane Street: Probability and Markets
  3. 03Citadel: Quantitative Research Interview Process
  4. 04FINRA: Understanding Settlement Cycles
  5. 05Jane Street — Quantitative Research
  6. 06Jane Street — Quantitative Researcher role
  7. 07Jane Street — Quantitative Trader role
  8. 08Citadel — Quantitative Research
  9. 09Citadel — Quantitative Research Analyst
  10. 10Two Sigma — Quantitative Research and Data Science
  11. 11Bridgewater — Investment Careers
  12. 12NIST — AI Risk Management Framework: Generative AI Profile
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