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AVP/Quantitative Researcher

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Onsite

AVP/Quantitative Researcher

Alliancebernstein

AVP/Quantitative Researcher

Skills

SQL QueriesPythonData ScienceMachine LearningKubernetesWorkdayApache Airflow

1 month ago

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Important information


Contract type:

Permanent

Location:

United Kingdom

Work mode:

Onsite

Published on:

14 September 2026

What they need


Who You’ll Work With

AllianceBernstein’s Systematic Fixed Income team develops and manages cutting-edge, high-performance, fully systematic, factor-driven fixed-income portfolios.

 

What You’ll Do

We are seeking a quantitative researcher focused on systematic fixed-income and credit strategies to join our London office. The successful candidate will collaborate with colleagues across the investment process and contribute to the development, implementation, and management of systematic strategies within AllianceBernstein’s Fixed Income division.

 

Responsibilities include, but are not limited to:

  • Developing and evaluating systematic investment strategies through simulations, backtesting, and strategy analysis.
  • Working on portfolio optimization, data science, and quantitative research problems.
  • Conducting factor discovery, factor return analysis, and risk attribution.
  • Contributing to our quantitative research environment, abAlphaLabs, a Python-based research platform.
  • Taking a hands-on role in the management and ongoing enhancement of systematic fixed-income strategies.

 

What We’re Looking For

The ideal candidate will have:

  • An advanced degree in Finance, Financial Engineering, Mathematics, Computer Science, Operations Research, Economics, Electrical Engineering, or a related field.
  • Strong Python programming skills and deep familiarity with the Python ecosystem.
  • Experience working with SQL databases.
  • Excellent attention to detail, a strong focus on quality, and the ability to take ownership of projects.
  • Knowledge of fixed-income securities and markets, which is preferred but not required.
  • Deep desire to understand and outperform the markets.
  • Data science and machine learning skills are a strong plus.
  • Exposure to modern development and operations tools, such as Airflow, Kubernetes, or similar technologies, is a plus.

 

Prior fixed-income trading or portfolio management experience is not required.

London, UK

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