Quantitative Specialist: Trading Systems & Analytics (NYC)

White Swan Data; New York (NY); On-site; USD 160,000 - 180,000; Full time

Benefits offered by this job

Annual discretionary bonus

25 days holiday per annum

Pension plan

Job summary

White Swan Data, a growing team of mathematicians, data scientists and software engineers, seeks a Quantitative Specialist in NYC to join a fast-developing trading systems initiative. You will develop mathematical models and high-performance algorithms, automate betting operations, and manage data generation, storage and analysis with back-testing and simulations.

This is a hands-on role in a small, entrepreneurial environment with autonomy to explore new ideas and contribute to the US

Qualifications

• Master's degree in mathematics, statistics, computer science, engineering, or another quantitative discipline.
• 1-2 years of professional experience in a quantitative role.
• Proficient with analytical programming languages such as R, Python, C++.

Responsibilities

• Acquire data from multiple data sources, filtering, cleaning and wrapping.
• Interpret data, analyse results using statistical techniques, and provide reports.
• Identify, analyse, and interpret trends or patterns in complex data sets.
• Work within the team to prioritise business and information needs.
• Identify process improvement opportunities.
• Design, build, test and deliver data processing and automation software.

Skills

Masters degree

Quantitative experience

R/Python/C++

Education

Masters in Math/Stats/CS/Engineering

Job description

White Swan Data, a growing team of mathematicians, data scientists and software engineers, seeks a Quantitative Specialist in NYC to join a fast-developing trading systems initiative. You will develop mathematical models and high-performance algorithms, automate betting operations, and manage data generation, storage and analysis with back-testing and simulations.

This is a hands-on role in a small, entrepreneurial environment with autonomy to explore new ideas and contribute to the US