Job details
Citi's Markets business is a leading global financial markets franchise, providing clients with a broad range of financial products and services across fixed income, currencies, commodities, equities, and prime finance. Within this dynamic environment, the Markets Quantitative Analytics team plays a critical role in developing and implementing cutting-edge quantitative models and analytical tools to support trading activities, risk management, and client solutions. This role is specifically situated within the Commodities sector, contributing to the innovative application of quantitative strategies in a rapidly evolving market landscape.
As an Algorithmic Trading Quantitative Analyst (Vice President) within our Commodities team in London, you will be instrumental in designing, developing, and optimizing advanced electronic market-making and algorithmic pricing models.
This is an exceptional opportunity to apply your quantitative expertise in a practical, production-oriented setting, directly impacting trading operations and risk management. You will work within a closely integrated team, gaining exposure to the microstructure of commodities markets and contributing to the expansion of systematic strategies in a leading financial institution. This role offers the chance to bridge sophisticated theoretical models with tangible, real-world trading outcomes, making a significant contribution to Citi's competitive edge in the global commodities market.
Primary Responsibilities of the role
- Research, design, and implement electronic market-making models, including hedging algorithms, bid-offer models, price predictors, and automated pricing frameworks for Commodities.
- Analyze the performance of existing models in actual market-making operations and provide recommendations for continuous improvement and optimization.
- Develop and extend functionality of current production models and build robust hedging strategies across various Commodity markets.
- Collaborate closely with traders, quants, and technologists to ensure models generate value, are optimally integrated, and are aligned with business objectives.
- Focus on thorough model testing and the practical implementation of appropriate models, ensuring their effectiveness and reliability in a live trading environment.
- Understand the balance between model sophistication and ease of implementation, striving for pragmatic solutions that achieve goals efficiently.
What we need from you
- Proven experience working in systematic trading, encompassing areas such as execution algorithms, statistical arbitrage, or electronic market making.
- Demonstrated success in solving practical problems, ideally within finance, using advanced statistical and machine learning techniques.
- Strong programming proficiency in Java/C++ and Python is essential, coupled with the ability to work effectively with large datasets.
- Proficiency in database applications, such as SQL and KDB, for data manipulation and analysis.
- M.S. or Ph.D. in a highly quantitative field such as mathematics, physics, statistics, engineering, or financial engineering.
- Attention to detail, strong problem-solving capabilities, and the ability to articulate complex quantitative concepts in simple terms to diverse stakeholders.
If you are actively working with clients, have a passion for relationships and want to be part of a successful global franchise – then apply today.
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
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Job Family Group:
Institutional Trading------------------------------------------------------
Job Family:
Quantitative Analysis------------------------------------------------------
Time Type:
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Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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