Historical Data Management Quantitative Analyst

Historical Data Management (HDM) team within Market & Counterparty Risk Analytics (MCRA) is responsible for Data Governance, the Target State Operating model, and the Historical Data Storage system to provision financial markets, macroeconomic and consensus data for risk models’ usage across market risk, credit risk, treasury risk, scenario design and expansion processes to meet risk management requirements and regulatory expectations.

The HDM team will partner with Risk Technology and Modelling teams in MCRA to design, implement, and optimize the market data management process using big data technology for data ingestion, data processing, data integration, data lake storage and data analytics.

The HDM Quantitative Analysis work stream will lead the effort to:

·         Manage historical market factor time-series across all products and all regions related to Market Risk IMA and Counterparty Risk IMM models. This includes defining market data sources, collecting data, validating data, and developing data cleansing logics.

·         Ensure that cleaned market factor data can meet regulatory requirements and can be used as the inputs for Citi’s IMA and IMM models.

·         Define market data sources and manage the Historical Data Storage system including design of data quality control and enhancement logic.

·         Develop and enhance quantitative methods for measuring and analysing the quality of historical market data used by various models across all Risk Modelling Analytics and Enterprise Scenario groups’ teams.

The Historical Data Management Quantitative Analyst's responsibilities include:

• 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.

What we will need from you:

• Educated to postgraduate level, with an excellent academic record in a quantitative field (e.g. mathematics, physics, computer science, statistics, econometrics, quantitative finance, etc.). Master or higher degree is strongly preferred.

• 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),

• 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.

• 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.

In return, 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

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Job Family Group:

Risk Management

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Job Family:

Risk Analytics, Modeling, and Validation

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Time Type:

Full time

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