Historical Data Management Quantitative Analyst, Citi

Citi

Location:
Poland, Warsaw

Category:
Finance

Contract Type:
Employment contract

Salary:

Not provided

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Job Description:

The Historical Data Management (HDM) team within Market & Counterparty Risk Analytics (MCRA) is responsible for Data Governance and Historical Data Storage system to provision financial markets, macroeconomic, and consensus data for risk models’ usage across various risk management and regulatory processes. The HDM Quantitative Analysis work stream leads efforts in managing historical market factor time-series, data quality control, and development of methods for measuring data quality while ensuring regulatory compliance.

Job Responsibility:

Conducting quantitative data analysis, including preparation of statistical and non-statistical data exploration, data validation, and identification of data quality issues
Report major data quality issues and follow up with the recommended actions
Analyzing and interpreting data reports, making recommendations addressing business needs
Work with project management team to ensure timely delivery of the project
Creating formal documentation for developed system, observing system reports and take actions, work with supporting Technology teams to address issues
Optimizing monitoring systems, document optimization solutions, and present results to non-technical audiences
write formal documentation using technical vocabulary
Introducing process automation of data extraction and data pre-processing tasks, performing ad-hoc data analyses to improve the processes, design and maintain complex data manipulation processes, and provide documentation and presentations
Help in training of junior quantitative analysts, sometimes also contributing to organization of their work, which may potentially include managing of junior team members

Requirements:

Educated to postgraduate level, with an excellent academic record in a quantitative field (e.g. mathematics, physics, computer science, statistics, econometrics, quantitative finance, etc.)
3+ years of relevant working experience, financial risk area is preferred
Programming experience with statistical analysis methods (team uses Python + SQL, knowing other languages, e.g. R, Matlab, VBA, may help but is not essential)
Keen interest in banking and finance, especially in the field of Risk Management
Consistently demonstrates clear and concise written and verbal communication skills
Self-motivated and detail oriented
Demonstrated project management and organizational skills and capability to handle multiple projects at one time

Nice to have:

Experience of one or more of the following is an advantage but not essential: risk management practices and procedures
numerical methods
Monte Carlo simulations
statistical hypotheses testing
derivative pricing and exotic products

What we offer:

Competitive salary & social benefits (e.g. private healthcare care, Benefit System, life insurance)
Work in a friendly and diversified environment, appreciating differences in style and perspective and using them to add value to decisions leading to organizational success
A great environment for learning new technology and tools, online and instructor led training opportunities
Working in a friendly, dynamic and multinational environment
Opportunity to have an influence on the way you perform your tasks - our teams are constantly looking for new and better ways and we encourage all improvement ideas
A chance to make a difference with various affinity networks and charity initiatives

Additional Information:

Job Posted:
May 01, 2025

Employment Type:

Fulltime

Work Type:

Hybrid work

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Historical Data Management Quantitative Analyst