Company Description
Axion Group, LLC is a global multi-manager platform that invests in quantitative trading strategies through both
internal and partner portfolio managers. For over 15 years, we have capitalized on market inefficiencies by leveraging
proprietary technology and infrastructure. Our portfolio spans multiple asset classes, reflecting our commitment to
innovation and precision in quantitative finance.
This role is ideal for individuals passionate about quantitative investing. It offers the chance to deepen expertise
across four core areas: data, statistics, technology, and financial markets.
Job Description
We are seeking a talented FX Data Scientist Intern with strong Python and data mining skills, who has a passion for
quantitative trading. This role involves working closely with a Senior Quantitative Portfolio Manager and Developer to
assess the quality of proprietary FX datasets and derive actionable insights.
Key Responsibilities:
● Analyze and assess the quality of proprietary FX datasets
● Extract meaningful insights to support quantitative trading strategies
● Collaborate with senior team members on the development and implementation of predictive models
Desired Skills and Experience:
● Strong understanding of FX market dynamics
● Previous experience with financial data and APIs in a systematic trading environment is highly desirable
● Proficiency in machine learning and statistics
● Proficiency in tools such as Python, Linux, Git, and time-series databases
● Experience working with large datasets and distributed computing environments
● Strong attention to detail, team-oriented, and quick learner
Education:
● B.S./M.S. in a technical discipline (Computer Science, Statistics, Mathematics, Engineering) from a top-tier
university
● Class of 2024 or 2025
Location:
● New York or Remote, depending on skillset
Compensation and Benefits:
● In accordance with New York City’s Pay Transparency Law, the weekly salary for this role is $**** to $****.
● Casual and friendly work environment
Job Type: Internship
