Credit Quantitative Analyst

Capula Ltd; Greater London; On-site; GBP 95,000 - 140,000; Full time

Benefits offered by this job

Salary and bonus scheme

Staff development and training

Gym membership and wellness space (in‑

Generous pension contribution

Free breakfast and lunch in employee餐厅

Private medical insurance

Job summary

Capula Ltd. is seeking a Credit Quantitative Analyst to strengthen our credit data and product infrastructure.

The role sits at the intersection of data engineering and quantitative structuring, owning core credit datasets and extending pricing capabilities into new products. You will build and operate a live data pipeline with ongoing QC, reconcile data from multiple sources, and develop pricers for credit products including CDS, ETFs and TRS.

Qualifications

• Degree in a quantitative discipline and experience building credit data pipelines.
• Proven experience maintaining point-in-time datasets through credit events and index rolls.
• Experience producing ETF total-return series with rates separated from credit return.
• Daily QC on a live credit dataset and production data pipeline.

Responsibilities

• Data cleanup & maintenance: build and maintain historical datasets for credit products (index rolls, defaults, recoveries, corporate actions).
• Reconcile data across sources (Markit, Bloomberg, dealer marks) for consistency and accuracy.
• Own day-to-day quality of the credit dataset as a live pipeline with ongoing QC.
• Product extension: build pricers and spread construction for credit products (CDS, ETFs, TRS, tranches) and future extensions.
• Support the future extension into credit futures and TRS on ETFs.

Skills

CDS pricing

Credit data ecosystem

Data reconciliation

Python

Education

Quantitative degree

Point-in-time data experience

ETF total-return knowledge

Live production QC

Tools

Bloomberg

Markit

Python

Job description

Duties and responsibilities

We are looking for a Credit Quantitative Analyst to strengthen the foundational data and product infrastructure underpinning our credit business. This role sits at the intersection of data engineering and quantitative structuring. You will both own the integrity of our core credit datasets and extend our pricing capabilities into new products. This is a hands‑on role suited to someone who has previously built and operated credit data infrastructure in a live, production environment (not simply consumed it for research).

• Data Cleanup & Maintenance: Build and maintain the historical dataset for all credit products, including index rolls, defaults and recoveries, and corporate actions.
• Reconcile data across multiple sources (Markit, Bloomberg, dealer marks) to ensure consistency and accuracy.
• Own the day‑to‑day quality of the credit dataset – both raw inputs and derived risk analytics, operating this as a live pipeline with ongoing QC, not a one‑off build.
• Product Extension: Build pricers and spread construction for credit products where coverage is currently limited, including: Credit ETFs / Total Return Swaps (TRS) including ground‑up z‑spread construction, with the rates component cleanly stripped out so the credit return is usable directly; Credit tranches; Clean single‑name CDS curves; Cash bonds mapped to the CDS universe; Support the future extension of this work into credit futures and TRS on ETFs.

Education and Qualifications

• A degree in a quantitative discipline.
• Experience: Proven experience building and maintaining point‑in‑time datasets (vol, tranche, single‑name CDS, and bond data) through actual credit events and index rolls - not just static historical data.
• Experience: Producing ETF total‑return series with the rates leg cleanly separated from the credit return.
• Experience: Running daily QC on a live credit dataset - i.e. having operated a data pipeline in production, rather than only having built one for a research exercise.

Skills

• Strong understanding of CDS option and/or tranche pricing models (you won’t necessarily need to build these from scratch given our existing infrastructure, but a solid grasp of the underlying mechanics is essential).
• Experience building and maintaining a credit data ecosystem from scratch – spanning bonds, single‑name CDS, tranches, and vol – ideally integrated into a “total return” framework that supports backtesting without extensive manual data conversion or cleaning.
• Strong reconciliation and data quality instincts; comfortable working across multiple data vendors and dealer sources.
• Solid programming skills (Python and/or similar) for building pricing and data pipeline tools.

Benefits

• A competitive salary and bonus scheme
• Excellent staff development and training opportunities
• Corporate gym membership (and a complimentary wellness space in our London office)
• Generous pension contribution
• Free breakfast and lunch in our employee restaurant
• Private medical insurance and other benefits

Capula is dedicated to helping all employees flourish in their roles by supporting your professional development. We will provide:

Capula is committed to fostering a collaborative and inclusive environment, providing employees with the opportunity to develop their skills and advance their careers in the financial sector. We actively promote equality of opportunity for all with the right mix of talent, skills and potential, and welcome applications from a wide range of candidates.