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Quantitative Analyst and Investment Data Scientist - Intern

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Tokio Marine Kiln


20d ago

🚀 Off-cycle Internship

New York

⌛ Closed
Applications are closed

Off-cycle Internship

Data•New York


  • This individual will be assisting portfolio managers with leveraging quantitative credit-risk modelling to develop systematic trading strategies in the credit space, focusing on US investment grade bonds.


  • Strong problem solving, analytical and quantitative skills.
  • Specialty in quantitative finance, statistics, computer science or related majors.
  • Working towards master’s degree or above.
  • Self-motivation and ability to work independently as well as a team member.
  • Strong interests in cutting edge technologies and their applications in finance.
  • Great communication, written and presentation skills to convey ideas precisely to the team members and senior management team.
  • Proficiency in Python, and familiar with database programming languages such as SQL, etc.
  • Basic knowledge of fixed income and credit investment.
  • Knowledge of machine learning frameworks (e.g. scikit-learn), and models such as Logistic Regression and NLP is a plus.
  • Experience working with open source libraries and distributed computing (e.g., AWS) is a plus.

Area of Responsibilities



  • Assist portfolio manager with management of a credit portfolio of US investment-grade bonds, research on credit-risk modelling and developing/improving way of quantitative investment decision making for credit investment
  • Generate innovative research ideas, evaluate current/new datasets, and perform strategy back tests/portfolio optimization/risk management, etc.
  • Implement ETL processes, manage databases, write clean, efficient and maintainable codes, and evaluate which of various technological methods are suitable to our purposes if needed
  • Work with technology vendors to manage existing cloud computing infrastructures and onboard new computing capabilities (such as AWS, etc.)


Work type

Full time

Work mode



New York