Latency Optimization and Execution Research Analyst
Singapore
Qube Research & Technologies
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.
Your future role within QRT:
We are seeking a Latency Optimization and Execution Research Analyst to optimize our trading infrastructure.
Responsibilities
- Writing code for the telemetry/monitoring/alerting systems that measure record and report various latency metrics.
- Analyze large data sets including market data feeds and order flows to provide inputs to optimize latencies across the full stack of trading execution.
- Post-order analysis to analyze missed opportunities and infer insights useful for improving connectivity setup and trading strategies.
Your present skillset:
- Degree in Computer Science, Engineering, or related field.
- Strong skills in Python, pandas.
- Experience working with large data sets including visualization in user interfaces.
- Experience in scaling large workloads with Ray,etc.
- Experience setting up and developing in a cloud environment like AWS.
- Experience of Data application frameworks -like DASH etc.
- Experience in machine learning.
- Experience in financial markets.
QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Computer Science Engineering Machine Learning Pandas Python Research Trading Strategies
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