Hybrid Rates Quant Strategist - Systematic Trading

SMBC

New York (NY)

Hybrid

USD 109,000 - 180,000

Full time

4 days ago
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Benefits offered by this job

Hybrid work model
Competitive benefits

Job summary

SMBC is seeking a Quantitative Researcher / Strategist in New York to join the Rates Systematic Trading team. You will research, develop, and implement quantitative models and electronic trading strategies across pricing, market making, alpha generation, execution, hedging, and risk management.

You will collaborate with Quantitative Traders and Technologists to bring ideas from research to production, with a strong emphasis on robust testing, documentation, and scalable solutions in a hybrid

Qualifications

  • Graduate degree in a quantitative field such as Financial Engineering, Math, Physics, Statistics, or CS.
  • Strong foundation in time-series, statistics, optimization, or machine learning.
  • Proficient in Java or other OO languages; capable of handling large datasets.

Responsibilities

  • Develop quantitative models for pricing, market making, execution, hedging, and risk.
  • Analyze market data to identify patterns and opportunities.
  • Research and implement alpha signals and systematic strategies for Rates products.
  • Build backtesting, simulation, and performance analysis frameworks.
  • Collaborate with traders and technologists to deliver production-ready solutions.
  • Maintain rigorous testing and documentation of methodologies and risks.

Skills

Quantitative analysis
Java programming
Statistical methods
Communication skills
Team collaboration

Education

MS or PhD in a quantitative field

Tools

Python
SQL
kdb+/q

Job description

SMBC is seeking a Quantitative Researcher / Strategist in New York to join the Rates Systematic Trading team. You will research, develop, and implement quantitative models and electronic trading strategies across pricing, market making, alpha generation, execution, hedging, and risk management.

You will collaborate with Quantitative Traders and Technologists to bring ideas from research to production, with a strong emphasis on robust testing, documentation, and scalable solutions in a hybrid

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