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Quant Researcher - FI

Job in City Of London, Central London, Greater London, England, UK
Listing for: Selby Jennings
Full Time position
Listed on 2026-10-01
Job specializations:
  • Finance & Banking
    Data Scientist
  • IT/Tech
    Data Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 110000 GBP Yearly GBP 80000.00 110000.00 YEAR
Job Description & How to Apply Below

Our client is a boutique investment firm that combines quantitative research, proprietary data infrastructure, and advanced analytics to support investment decision-making across fixed income markets.

The firm has invested heavily in building an in-house research environment that integrates high-quality market data, rigorous analytical frameworks, and AI-enabled workflows to generate differentiated investment insights.

The investment team places a strong emphasis on data integrity, research discipline, and robust validation processes. Researchers work closely with senior investment professionals and play a direct role in determining which analytical findings ultimately influence portfolio construction and capital allocation decisions.

The Opportunity

This role sits at the heart of the firm's quantitative research process and serves as the primary expert on fixed income data quality, analytical standards, and model validation. Unlike traditional quantitative research positions focused on alpha generation or model development, this role is responsible for ensuring that research outputs, data inputs, and model conclusions are statistically robust, economically meaningful, and suitable for real-world implementation.

You will work closely with quantitative researchers, senior investment professionals, and technology teams to define analytical standards, validate datasets, assess model outputs, and maintain the frameworks that determine whether investment signals are suitable for deployment. The position offers significant exposure to fixed income markets, quantitative research methodologies, and portfolio management decision-making.

About the Company

Our client is a boutique investment firm that combines quantitative research, proprietary data infrastructure, and advanced analytics to support investment decision-making across fixed income markets.

The firm has invested heavily in building an in-house research environment that integrates high-quality market data, rigorous analytical frameworks, and AI-enabled workflows to generate differentiated investment insights.

The investment team places a strong emphasis on data integrity, research discipline, and robust validation processes. Researchers work closely with senior investment professionals and play a direct role in determining which analytical findings ultimately influence portfolio construction and capital allocation decisions.

Key Responsibilities Fixed Income Data Expertise
  • Act as the firm's subject matter expert on fixed income datasets and market analytics.
  • Define analytical requirements for the data structures used by quantitative research teams.
  • Specify how returns, spreads, ratings, fundamentals, call schedules, and benchmark data should be constructed and maintained.
  • Ensure data is correctly aligned to decision dates and reflects point-in-time information.
  • Establish standards governing the handling of issuer events and fixed income security characteristics.
Data Validation and Quality Control
  • Design and implement rigorous validation procedures for fixed income datasets.
  • Reconcile datasets against independent sources and identify discrepancies.
  • Develop systematic checks to identify data gaps, pricing anomalies, and inconsistencies before they impact research outputs.
  • Monitor ongoing data quality and ensure analytical datasets maintain the highest standards of accuracy.
  • Work closely with technology teams to address issues identified through validation processes.
Backtesting and Research Evaluation
  • Own and enhance the firm's research evaluation and backtesting framework.
  • Ensure research methodologies eliminate look-ahead bias and maintain point-in-time integrity.
  • Design realistic transaction-cost assumptions and implementation frameworks.
  • Evaluate…
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