Quantitative Researcher - High Frequency Trading

On behalf of a top-tier quantitative hedge fund we are seeking an experienced quant researcher. Important points to note: This role will be based in Shanghai (full relocation package available). Candidates must speak Mandarin to a minimum of business level. The compensation package will match international norms for the industry. You will have a demonstrable track record of alpha generation from a top-tier hedge fund, prop trading house, asset manager or sell-side trading desk. Role: My client i

Madison Pearl - Hong Kong - Full time

Salary: Extremely competitive and in line with international norms

On behalf of a top-tier quantitative hedge fund we are seeking an experienced quant researcher.

Important points to note:

  1. This role will be based in Shanghai (full relocation package available).
  2. Candidates must speak Mandarin to a minimum of business level.
  3. The compensation package will match international norms for the industry.
  4. You will have a demonstrable track record of alpha generation from a top-tier hedge fund, prop trading house, asset manager or sell-side trading desk.

Role:

  1. My client is a dynamic quantitative trading firm with a significant AUM. They are expanding their team and are looking for experienced Quantitative Researchers to help build models, strategies and systems that price and trade global futures.
  2. The fund trades multiple asset classes but have a bias towards global equities and derivatives.
  3. You will apply your experience in experiment design, dataset generation, time series analysis, feature engineering and model building to financial datasets.
  4. Manage development of research tools and applications for processing large data sets.
  5. Direct alpha research geared towards high frequency, high-volume and scalable strategies

Requirements:

  1. 3+ years experience as a Quant Researcher at a Tier-1 HFT firm / multi-manager platform.
  2. Demonstrable success in developing strategies within the high-frequency to mid-frequency space (seconds to intraday).
  3. Deep understanding of the critical technical components of a high-frequency trading pipeline - from data ingestion to order execution.
  4. Very high proficiency in statistical modeling applied to time-series data machine learning architecture.
  5. Masters degree, or above, in a quantitative field (Maths, Physics, Computer Science, or Engineering etc.).
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