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Jobs(31,365)/Senior Data Scientist Role(384)/DRW (54) - Senior Quantitative Developer
DRW

DRW - Senior Quantitative Developer

Singapore+ Equity5mo ago
In OfficeSeniorAPACHedge FundDiagnosticsSenior Data ScientistObservable

Requirements

• 5+ years of hands-on experience in a hedge fund, proprietary trading firm, or sell-side trading or electronic execution team, with direct responsibility for production trading infrastructure • Proven experience designing, building, and operating live trading systems • Excellent logical reasoning, strong quantitative and analytical skills • Data ingestion, validation, and normalization • Backtesting and simulation • Portfolio construction and constraint enforcement • Execution integration and live trading support • Strong engineering discipline and ability to work independently with minimal guidance. • Meticulous attention to details and accuracy in work • Excellent verbal and written communication skills, with the ability to effectively interact with the global team • Ability to adapt in a fast-paced, collaborative, and results-oriented environment, and thrive under time-sensitive and high-pressure situations • For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice. • California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice. • #LI-PR1

Responsibilities

• Architect, implement, and maintain end-to-end production infrastructure for mid-frequency equity statistical arbitrage strategies • Build and optimize large-scale data pipelines for market, fundamental, and alternative datasets • Develop and maintain research and back testing platforms with realistic transaction cost, execution, and constraint modeling • Integrate strategies with execution systems and order management, and support real-time trading and monitoring • Ensure production systems are performant, reliable, observable, and operationally robust • Build tooling for diagnostics, performance attribution, and post-trade analysis • Continuously improve system design, scalability, and operational resilience.

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