Credit Quantitative Analyst

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).

• 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.

• 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.

• A degree in a quantitative discipline. 

• 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.

• 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.