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Trexquant Investment LP
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Trexquant Investment LP एक मात्रात्मक निवेश प्रबंधन फर्म है, जो सांख्यिकीय आर्बिट्राज और मध्यम-आवृत्ति ट्रेडिंग पर केंद्रित है। इसका शोध-आधारित दृष्टिकोण विविध बाज़ार डेटा से तैयार किए गए हज़ारों ट्रेडिंग संकेतों, या अल्फाज़, को बदलती बाज़ार परिस्थितियों में मजबूती के लिए कठोर बैकटेस्टिंग के साथ जोड़ता है। फर्म इन रणनीतियों को संयुक्त राज्य अमेरिका, यूरोप, जापान, ऑस्ट्रेलिया और कनाडा सहित वैश्विक बाज़ारों में 5,500 से अधिक कैश इक्विटी पोज़िशनों पर लागू करती है।
LinkedIn
कंपनी की नौकरियाँ

Data Engineer in Beijing (Hybrid)

Build scalable pipelines for Trexquant’s financial and alternative datasets in a hybrid Beijing role. Support quantitative research with reliable, normalized data infrastructure.

CNचीनहाइब्रिडपूर्णकालिकजूनियरमध्य स्तरआवश्यक भाषा: अंग्रेज़ीडेटा इंजीनियर
ETLLinuxPythonSQL

विवरण

  • Create, operate, and enhance scalable ingestion pipelines for market, reference, tick, and alternative data supplied by external vendors.
  • Manage the normalization, validation, storage, and lifecycle of research datasets so they remain accurate, consistent, and accessible for quantitative research and simulation.
  • Develop and tune Python and SQL data-processing workflows across equities, options, futures, fixed income, ETFs, and foreign exchange.
  • Work with quantitative researchers, data architects, and infrastructure engineers to onboard datasets, strengthen data quality, and provide dependable research-ready data.
  • Implement monitoring, automation, and operational tools that support the reliability, performance, and scalability of the firm’s data platform.
  • Document pipelines and engineering practices while helping advance Trexquant’s research data infrastructure.

आवश्यकताएँ

  • Bachelor’s or master’s degree in computer science, engineering, mathematics, or a related quantitative discipline.
  • At least two years of data engineering experience in systematic trading, quantitative research, hedge funds, or financial technology.
  • Experience using Python and SQL to build large-scale data ingestion and ETL pipelines.
  • Strong Linux skills, including scripting, automation, and operation of production data-processing systems.
  • Thorough understanding of financial data across equities, options, futures, fixed income, ETFs, foreign exchange, and alternative datasets.
  • Experience handling market, tick, reference, and vendor data feeds, including normalization, validation, and quality control.
  • Familiarity with modern storage formats and technologies such as Parquet, Arrow, object storage, and columnar databases.
  • Strong communication and collaboration skills for working effectively with research and engineering teams.
  • Fluency in English.

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