FID, Quantitative Trading Desk Strategist

Morgan StanleyNew York, NY
1d$150,000 - $250,000

About The Position

The Fixed Income Division is comprised of Interest Rate and Currency Products, Credit Products and Distribution. Professionals in the Division assess and actively manage risk, trade securities, and structure as well as execute innovative transactions in the fast-paced and constantly changing global markets. Morgan Stanley aligns its municipal investment banking, underwriting, sales, trading, lending, and M&A advisory in one integrated organizational group under the umbrella of the Municipal Securities Division. Imagine you run a grocery store. Every decision costs money. Too many carrots? Waste. Too few? Missed profit. Discount too early? You leave money on the table. Discount too late? You’re stale bread into the trash. Now imagine this grocery store trades bonds, derivatives, and ETFs not bananas. We don’t worry about spoiled produce — but we do worry about inventory risk, market impact, and whether today’s profits makes sense given the decisions we made yesterday. Prices move. Competitors react. Models lie (sometimes). Data tells stories — if you know how to listen. That’s where you come in. You’ll sit on a trading desk and help answer questions like: How much inventory should we carry right now? Which positions are quietly printing money, and which ones are fooling us? What happens to P&L if yields move, volatility spikes, or the guy across the street starts dumping inventory? Are we actually being smart… or just getting lucky? You’ll build models, measure performance, explain results, and influence daily trading decisions — not from a distance, but in real time, with real consequences.

Requirements

  • Master’s Mathematics, Physics, Engineering, or something similarly quantitative
  • Strong Python skills — you can go from idea → code
  • Solid grounding in probability, statistics, and numerical modeling
  • You enjoy telling stories with data
  • Familiarity with bonds, ETFs, and derivatives (or the ability to learn them fast)
  • You’re comfortable having your ideas questioned — and questioning others
  • A genuinely good sense of humor (not optional)

Nice To Haves

  • kdb/q experience
  • Machine learning techniques like random forests or logistic regression

Responsibilities

  • Build models
  • Measure performance
  • Explain results
  • Influence daily trading decisions
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