AVP/Quantitative Researcher
At a glance
Mid-level Data Science role at Abglobal. London · full-time · no salary stated · we estimate £70,750–£131,900.
Abglobal has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build and test systematic fixed-income and credit strategies using simulations, backtests and strategy reviews
- Tackle portfolio optimization and quantitative research questions, including data science work
- Identify investment factors, study their returns and assess how they contribute to risk
- Use and improve the Python-based abAlphaLabs research platform
- Help run and refine systematic fixed-income strategies over time
What you bring
- An advanced degree in finance, mathematics, computer science or another listed field
- Strong Python skills and substantial familiarity with its ecosystem
- Experience working with SQL databases
Who this fits
This role suits a quantitative researcher interested in systematic fixed-income and credit strategies, with a focus on careful, high-quality work and taking project ownership. It is based in London. Fixed-income market knowledge is helpful but optional; prior trading or portfolio-management experience is not required.
From the employer
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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