Markets Quantitative Analysis Department (MQA) is a division of the Global Markets business and has responsibility for providing the analytical models which are used for pricing securities and risk managing the Firm’s positions throughout the Markets’ businesses. The scope of this work extends from the research into the mathematical derivation of the model, through the coding, testing, and documentation of the model for formal validation and approval, and finally to delivering the model both to the desktop and to Technology for incorporation into the Firm’s books and records systems. MQA’s responsibilities span the G10 Rates, Local Markets, Credit, Commodities, FX, Equity, Equity Hybrids and Mortgage/Securitized markets businesses.

MQA Budapest is an integral part of the global structure of the department and plays a key role in the development of the core tools, processes, and analytics.

Responsibilities:

• Development and maintenance of the in-house python analytical infrastructure
• Advancing the quantitative toolbox by developing new technologies, algorithms, and numerical techniques
• Focus on Regulatory and Governance based projects.
• Work with Quant teams to standardize regulatory and infrastructural solutions.
• Cooperate with less technical team members to resolve problems.
• Extensive training will be given to the candidate in Budapest. The candidate will have daily contacts with supervisor(s) and will receive interactive training from various members of the Global team, including introduction and intermediary financial courses as well as Business training. The candidate will also participate to the team weekly meetings across regions.

Qualifications:

• Prior relevant experience in a Quantitative Developer role, or alternatively a python developer position
• Good command of programming using Python. Understanding async code, experience with pytest
• Familiarity of Linux/Windows
• Understanding distributed infrastructure components: MQs, Service discovery, Python Celery or similar, MongoDB, S3 is an advantage.
• Proven track record of development and support analytics library such as Rates, Credit, Equities, Commodities is an advantage.
• Previous experience working on Regulatory based projects such as Model Risk, Basel III, Stress Testing, CCAR, PAA is an advantage.

Education:

• MSc / BSc in Mathematics, Physics, Engineering, Finance, Economics or Computer Science

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