Desk Quant Analyst: Trading Systems & Data Insight

SQUAREPOINT SERVICES SINGAPORE PTE. LTD.

Singapore

On-site

SGD 120,000 - 180,000

Full time

3 days ago
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Job summary

Squarepoint is seeking a Desk Quant Analyst to maintain and upgrade the trading framework and manage large research and production datasets. You will monitor live and historical trading activity and support post-trade reconciliation in a fast-paced environment.

Collaborating with quant researchers and traders across regions, you will contribute to expanding systematic trading activities, ensuring robustness and data integrity under pressure.

Qualifications

  • Degree in Engineering, Computer Science or related technical subject.
  • Programming proficiency with at least one major programming or scripting language (e.g. C++, Java, Python).
  • Great attention to details.
  • Strong communication skills and ability to work well with colleagues across multiple regions.
  • Ability to work well under pressure.

Responsibilities

  • Maintain and upgrade the codebase and configuration of strategies within the firm’s automated trading framework.
  • Manage large datasets used in both research and production environments.
  • Perform live as well as historical monitoring of trading activities, including post-trade analysis or production reconciliation.
  • Work in close collaboration with quant researchers and traders to understand evolving needs of the trading desks.

Skills

C++/Java/Python
Attention to detail
Strong communication
Ability to work under pressure

Education

Engineering or Computer Science degree

Tools

Q/KDB+
Linux
Bash

Job description

Squarepoint is seeking a Desk Quant Analyst to maintain and upgrade the trading framework and manage large research and production datasets. You will monitor live and historical trading activity and support post-trade reconciliation in a fast-paced environment.

Collaborating with quant researchers and traders across regions, you will contribute to expanding systematic trading activities, ensuring robustness and data integrity under pressure.

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