Citi’s Risk Management organization oversees risk-taking activities and assesses risks and issues independently of the front line units.  We establish and maintain the enterprise risk management framework that ensures the ability to consistently identify, measure, monitor, control and report material aggregate risks.

We’re currently looking for a high caliber professional to join our team as Vice President, Historical Data Management Lead -  Hybrid (Internal Job Title: Model/Anlys/Valid Officer - C13) based in Taguig, Philippines. 

In this role, you’re expected to:

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 partners with Risk Technology and Modelling teams in Risk Management 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 engineering 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 analyzing the quality of historical market data used by various models across all Risk Modelling Analytics and Enterprise Scenario groups’ teams.

The Market Risk Data Engineering Manager is responsible for the direction, coordination, implementation, control, and completion of the historic market data management workflows in one of two subareas (macro or micro) while remaining aligned with the strategy, commitments, and goals of the MCRA group. Workflows include BAU work (data quality control and assurance, up to 1/3 of monthly time) as well as strategic projects: development of analytical tools, data migrations, new data onboarding, process improvement, system improvement and organizational change.

The Market Risk Data Engineering Manager’s responsibilities include:

• Taking ownership of several workflows in the Historic Data Management team in one of two subareas: macro or micro market factors
• Managing the work of team members involved in owned workflows and training of junior team members.
• Identifying and assigning project tasks based on the skill set, experience, and strengths of team members.
• Leading and supervising quantitative data analysis, including the preparation of statistical and nonstatistical data exploration, data validation, and the identification of data quality issues.
• Developing detailed project plans based on the current data system state reflected in data reports and making recommendations addressing business needs.
• Monitoring project implementation performance to ensure timely delivery and creating project status reports for internal team needs.
• Developing excellent leadership, internal customer relationships and communication skills to liaise effectively with all market data system stakeholders.
• Designing data solutions and analytics solutions and creating formal documentation for developed systems.
• Introducing process automation of data extraction and data pre-processing tasks.
• Coordinating ad-hoc data analyses to improve core processes, and the design and maintenance of complex data manipulation

As a successful candidate, you’d ideally have the following skills and exposure:

• Educated to postgraduate level, with an excellent academic record in a quantitative field (e.g. econometrics, statistics, data science, computer science, quantitative finance, mathematics, etc.).
• Master or higher degree is strongly preferred.
• 8+ years of relevant working experience (technology or data science area) for Banking or Insurance companies or Consulting clients in these industries.
• People management experience is a plus.
• Experience of work coordination of programmers / data scientists (especially in Python & SQL, knowing R, Matlab, VBA)
• Experience of one or more of the following is an advantage: Money Market Financial Instruments, Interest Rates Derivatives, Big data, Systems Design, Data Architecture, Process Reengineering, Project Management, Risk and Finance Data Management.
• Keen interest in banking and finance, especially in the field of Risk Management.
• Proficiency in inventory control and process improvement.
• Consistently demonstrates clear and concise written and verbal communication skills.
• Must be willing to work on EMEA work hours (start of shift around 12PM)

Take the next step in your career, apply for this role at Citi today

https://jobs.citi.com/dei

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Job Family Group:

Risk Management

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Job Family:

Model Development and Analytics

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Time Type:

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Most Relevant Skills

Analytical Thinking, Business Acumen, Constructive Debate, Data Analysis, Escalation Management, Policy and Procedure, Policy and Regulation, Risk Controls and Monitors, Risk Identification and Assessment, Statistics.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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