Desk Head Quantitative Advisor - Corporate & Investment banking - New York, New York, United States

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. Responsibilities 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, and integrating relative value, liquidity, and pricing analytics into trading workflows. Work closely with global technology, quantitative, and trading teams to align development efforts, ensuring the platform reflects regional differences in market structure, liquidity, regulation, and data availability, and establish coordination frameworks and development standards to promote consistency across geographies while allowing for localized model calibration and execution approaches. Develop 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. 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, including constraint‑aware portfolio optimization and building technology supporting ETF primary market activity, basket construction, pricing, creation/redemption workflows, NAV alignment, and arbitrage identification. Build tools to identify, test, and deploy systematic strategies across a broad product universe (single bonds, ETFs, CDS/CDX, credit derivatives), supporting relative value, basis, arbitrage, and volatility‑driven approaches. 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 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, and ability to operate effectively in a global, cross‑functional environment. 8+ years of experience in systematic/algorithmic credit trading and related quantitative strategy and systems development. Strong track record of building real‑time trading systems or algorithmic platforms, with solid programming skills in Python, C++, or Java, and a strong foundation in quantitative methods, portfolio construction, and optimization. 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. Benefits Base salary range does not include overtime pay, bonus and/or other benefits, where applicable. Actual base salary offer will vary based on skills and experience. The role is eligible for an annual discretionary bonus and includes a competitive benefits package including 401(k) plan with company match, medical/dental/vision, and other benefits for fertility, wellness, student loans and commuters. Inclusive Recruitment Statement Societe Generale is committed to offering an inclusive recruitment experience to all candidates. If you require any reasonable accommodations during the recruitment process, please do not hesitate to let our Recruiters know. #J-18808-Ljbffr SGS Société Générale de Surveillance SA