Job Information
Citigroup MQA Python Quantitative Developer (VP) in Budapest, Hungary
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.
As a MQA Python Quantitative Developer you will
be responsible for development and maintenance of the in-house python Analytical infrastructure
Advance 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 junior Quant Developer colleagues and less technical team members to resolve problems.
Participate on extensive training. 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.
Ideal background
PhD / MSc in Mathematics, Physics, Engineering, Finance, Economics or Computer Science
3-5 years relevant experience in a Quantitative Developer role, or alternatively a senior developer in a distributed computing position
Good command of programming using Python. Understanding async code, experience with pytest
Understanding distributed infrastructure components: MQs, Service discovery, Python Celery or similar, MongoDB, S3
System level familiarity of Linux/Windows
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.
What we can offer you
By joining Citi Hungary, you will not only be part of a business casual workplace with a hybrid working model (up to 2 days working at home per week), but also receive a competitive compensation package and enjoy a whole host of additional benefits that support you (and your family) to be well, live well and save well:
Cafeteria Program
Home Office Allowance (for colleagues working in hybrid work models)
Paid Parental Leave Program (maternity and paternity leave)
Private Medical Care Program and onsite medical rooms at our offices
Pension Plan Contribution to voluntary pension fund
Group Life Insurance
Employee Assistance Program
Access to a wide variety of learning and development programs, online course libraries and upskilling platforms, such as Udemy and Degreed
Flexible work arrangements to support you in managing work - life balance
Career progression opportunities across geographies and business lines
Socially active employee communities with diverse networking opportunities
Alongside these benefits Citi is committed to ensuring our workplace is where everyone feels comfortable coming to work as their whole self every day. We want the best talent around the world to be energized to join us, motivated to stay, and empowered to thrive.
Sounds like Citi has everything you need? Then apply to discover the true extent of your capabilities.
#LI-EK2
Job Family Group:
Institutional Trading
Job Family:
Quantitative Analysis
Time Type:
Full time
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Citi is an equal opportunity and affirmative action employer.
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