About this role
The engineer will apply data-driven methodologies to understand and optimize trading technology and real-time interactions with financial markets globally. Key tasks include analyzing network captures, automating metric collection, formulating controlled experiments, and improving trading strategy fill rates.
Candidates must possess a degree in Data Analytics or a related field and have experience collecting and interpreting network or financial market data. Proficiency in Python, data libraries (Pandas, Numpy/Scipy), and basic knowledge of TCP/UDP protocols are required.
What they're looking for
Data AnalyticsStatisticsData VisualizationTCPUDPPythonPandasNumpy
Frequently asked questions
What does a Quantitative Latency Engineer at Hudson River Trading do?
The engineer will apply data-driven methodologies to understand and optimize trading technology and real-time interactions with financial markets globally. Key tasks include analyzing network captures, automating metric collection, formulating controlled experiments, and improving trading strategy f…
What skills does this Quantitative Latency Engineer role need?
Key skills for this role include Data Analytics, Statistics, Data Visualization, TCP, UDP, Python.
How much does a Quantitative Latency Engineer at Hudson River Trading pay?
The employer did not list a salary for this role. Most similar Singapore roles publish their band on the job page.
Is this Quantitative Latency Engineer role remote, hybrid, or on-site?
This role is on-site, based in Austin.
How do I apply for this Quantitative Latency Engineer role?
You can apply directly on Hudson River Trading's careers page. ApplyLah can tailor your résumé and cover letter to this exact role in seconds first.