Temporary Algorithmic Trading Quant Jobs (NOW HIRING)

DIVISION DESCRIPTION: 

Global Banking and Advisory (GLBA) combines recognized wholesale coverage with world-class product, financing, and advisory expertise within one team, enabling us to best support our clients. On the one hand, our transversal, product-neutral coverage teams span all businesses to promote the bank's products and services to our clients globally, and on the other, we provide world-class capital raising, financing and advisory expertise.

We are seeking an experienced Systematic Trading Systems Strategist / Head of Algorithmic Trading Technology to lead the design and development of a next-generation systematic trading platform focused on U.S. investment-grade corporate credit.  This role sits at the intersection of quantitative research, trading, and technology, with a mandate to scale real-time trading capabilities across cash bonds, ETFs, and credit derivatives. The position is highly cross-functional and involves close collaboration with global teams to build a consistent and scalable systematic framework across regions.

Responsibilities: 
You will lead the end-to-end build-out of a systematic trading platform for spread-based investment-grade corporate bonds in the U.S., developing scalable infrastructure across signal generation, pricing, execution, portfolio construction, and risk management. This includes integrating relative value, liquidity, and pricing analytics into trading workflows.

You will work closely with global technology, quant, and trading teams to align development efforts, ensuring the platform reflects regional differences in market structure, liquidity, regulation, and data availability. You will also establish coordination frameworks and development standards to promote consistency across geographies while allowing for localized model calibration and execution approaches.

A central aspect of the role will be the development of real-time signal optimization and pricing frameworks, enhancing price formation through dynamic fair value models, liquidity-aware adjustments, and execution-sensitive signals embedded directly into trader decision-making tools.

You will develop portfolio trading and risk optimization capabilities to support efficient basket execution across credit markets, alongside robust hedging frameworks spanning factor-based, spread-based, and cross-asset strategies using ETFs, CDS, and indices. This includes implementing constraint-aware portfolio optimization and building technology supporting ETF primary market activity, including basket construction, pricing, creation/redemption workflows, NAV alignment, and arbitrage identification.

In parallel, you will build tools to identify, test, and deploy systematic strategies across a broad product universe, including single bonds, ETFs, CDS/CDX, and credit derivatives, supporting relative value, basis, arbitrage, and volatility-driven approaches.

You will also design and enhance execution strategies tailored to fixed income markets, addressing fragmented liquidity and RFQ-driven workflows, while improving performance through data-driven analytics, feedback loops, and transaction cost analysis, including portfolio-level execution for basket and ETF-related flows.

Skills and Qualifications:

The ideal candidate brings significant experience in systematic or algorithmic trading, with deep expertise in fixed income markets, particularly investment-grade credit, credit derivatives, and ETF market structure. Experience with portfolio trading, ETF primary market mechanics, or relative value strategies is highly valued, as is the ability to operate effectively in a global, cross-functional environment.

You have 8 years of experience in systematic/algorithmic credit trading and related quantitative strategy and systems development. 

You have a strong track record of building real-time trading systems or algorithmic platforms, along with solid programming skills (Python, C , or Java) and a strong foundation in quantitative methods, portfolio construction, and optimization.
You hold an advanced degree in computer science, engineering, quantitative finance, mathematics, or related field.

Must Have:

Advanced degree in Computer Science, Engineering, Mathematics, Finance, or related field.

8-15 years of experience in systematic trading, algorithmic trading, or quantitative strategy development.

Deep knowledge of fixed income markets, particularly, investment grade corporate bonds, credit derivatives (CDS/CDX), fixed income ETFs and ETF mechanisms (create/redeem)

Proven experience building real-time trading systems or algorithmic platforms.

Ability to translate quantitative insights into production-grade systems.

Strong understanding of cross-asset linkages (cash bonds, ETFs, derivatives).

Excellent cross-functional communication skills.

Strong problem-solving capability in complex, real-time environments.

Nice to Have:

Familiarity with machine learning applications in trading and signal generation.

Prior leadership experience in a global, multi-team environment.
Proficiency in French. 
Series 7, 63, and 57.