Durlston Partners
Quantitative Researcher – High-Frequency Trading (HFT) - NY/US
Vacancies across Futures, Equities, Options, Macro and others
Role Overview: As a Quantitative Researcher, you will develop and implement statistical models and algorithmic strategies to identify trading opportunities in real-time markets. You will work closely with software engineers and traders to optimize performance and continuously improve our trading systems.
Key Responsibilities:
Research, design, and implement predictive models using advanced statistical and machine learning techniques.
Analyze large volumes of market data to identify alpha signals and inefficiencies.
Conduct rigorous backtesting to evaluate strategy performance and robustness.
Collaborate with engineering teams to deploy strategies in production environments with low-latency constraints.
Monitor and refine models based on real-time performance and changing market conditions.
Requirements:
PhD or Master’s degree in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, or Electrical Engineering.
Strong programming skills in Python, C++, or similar languages.
Deep understanding of probability theory, stochastic processes, optimization, and statistical inference.
Experience working with large datasets and time-series data.
Familiarity with financial markets; prior experience in high-frequency trading or a similar quantitative trading environment is highly desirable.
Strong analytical and problem‑solving skills, with a bias for action and experimentation.
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Information Technology, Finance, and Research
Industries: Financial Services and Capital Markets
Location: New York, United States
Salary: $150,000.00-$200,000.00
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Role Overview: As a Quantitative Researcher, you will develop and implement statistical models and algorithmic strategies to identify trading opportunities in real-time markets. You will work closely with software engineers and traders to optimize performance and continuously improve our trading systems.
Key Responsibilities:
Research, design, and implement predictive models using advanced statistical and machine learning techniques.
Analyze large volumes of market data to identify alpha signals and inefficiencies.
Conduct rigorous backtesting to evaluate strategy performance and robustness.
Collaborate with engineering teams to deploy strategies in production environments with low-latency constraints.
Monitor and refine models based on real-time performance and changing market conditions.
Requirements:
PhD or Master’s degree in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, or Electrical Engineering.
Strong programming skills in Python, C++, or similar languages.
Deep understanding of probability theory, stochastic processes, optimization, and statistical inference.
Experience working with large datasets and time-series data.
Familiarity with financial markets; prior experience in high-frequency trading or a similar quantitative trading environment is highly desirable.
Strong analytical and problem‑solving skills, with a bias for action and experimentation.
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Information Technology, Finance, and Research
Industries: Financial Services and Capital Markets
Location: New York, United States
Salary: $150,000.00-$200,000.00
#J-18808-Ljbffr