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Two Sigma

Quantitative finance firm building predictive models

Quantitative Researcher - Quantitative Macro & Fixed Income

Quantitative ResearchConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • At least four years of quantitative research experience in macro markets, such as futures, foreign exchange, fixed income, or commodities.
  • Expertise in data analysis, time series analysis, and machine learning techniques.
  • An advanced degree in a quantitative discipline such as statistics, mathematics, physics, computer science, financial engineering, or a similar field.
  • Strong skills in at least one programming language, such as Python.
  • Ability to tackle in-depth research projects, discover creative solutions, and communicate complex ideas clearly.

Responsibilities

  • Develop innovative models to generate alpha in macro markets.
  • Contribute to the end-to-end investment process, including idea generation, feature development, alpha forecasting, monetization, portfolio construction, and portfolio management.
  • Analyze a vast array of datasets to discover alpha opportunities.
  • Apply advanced artificial intelligence and machine learning techniques to quantitative macro investing.
  • Collaborate in an entrepreneurial team environment with quantitative researchers and developers.

Desired Qualifications

  • Experience using AI-native and agentic workflows.

About the Company

Two Sigma

Quantitative finance firm building predictive models

Two Sigma is a financial sciences firm that uses data analysis, rigorous inquiry, and invention to tackle complex problems in investment management, securities, private equity, insurance technology, and venture capital. Its product approach centers on building sophisticated predictive models powered by extraordinary computing power and vast data. Modelers and engineers test ideas with information and iterative improvement to drive progress. Compared with many peers, Two Sigma differentiates itself through a data-driven, model-centric investment process that relies on large-scale computing and extensive datasets rather than relying on traditional methods alone. The company aims to solve the toughest challenges in its fields and advance investment outcomes by continuously refining predictive models through experimentation.

Company size
1,001-5,000
Company stage
Not listed
Total funding
$378.2M
Headquarters
New York City, New York
Founded
2001

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