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Quantitative Researcher - Quantitative Macro & Fixed Income

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Hybrid

Quantitative Researcher - Quantitative Macro & Fixed Income

Two Sigma

Quantitative Researcher - Quantitative Macro & Fixed Income

Skills

PythonData AnalysisMachine LearningAI

17 days ago

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Important information


Contract type:

Permanent

Location:

New York, NY, USA

Work mode:

Hybrid

Published on:

8 October 2026

What they need


Position Summary

Two Sigma is a leading quantitative investment management and trading firm. The company applies a scientific approach to investing, combining cutting-edge technology, artificial intelligence, data science, and quantitative research with rigorous human inquiry to capitalize on market opportunities and deliver alpha for investors.

Our team of engineers, quantitative researchers and data scientists looks beyond the traditional to test hypotheses and develop creative solutions to some of the world’s most complex economic problems.

We are looking for a quantitative researcher with an excellent background in statistical techniques and data analysis to join our Quantitative Macro & Fixed Income team. In this role, you will navigate the full research process and apply a rigorous scientific approach to design investment models trading a variety of global macro markets.

You Will Take On The Following 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

You Should Possess The Following Qualifications

  • 4+ years of quantitative research experience in macro markets (e.g., Futures, FX, Fixed Income, Commodities, etc.)
  • Expertise in data analysis, time series analysis, and machine learning techniques
  • Advanced degree in a quantitative discipline like statistics, mathematics, physics, computer science, financial engineering, or similar
  • Strong skills in at least one programming language (e.g., Python)
  • Experience using AI-native and agentic workflows is a plus
  • Ability to tackle in-depth research projects, discover creative solutions, and communicate complex ideas clearly

You Will Enjoy The Following Benefits

  • Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life & disability insurance
  • Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms
  • Learning: Tuition reimbursement, conference and training sponsorship
  • Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves
  • Hybrid Work Policy: Flexible in-office days with budget for home office setup

The base pay for this role will be between $165,000 and $300,000. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.

We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.

Two Sigma is committed to providing reasonable accommodations to qualified individuals in accordance with applicable federal, state, and local laws.

If you believe you need an accommodation, please visit our website for additional information.

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