Senior Market Data Analyst – VP

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Full time
Location: London
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Job offered by: ING Bank N.V.
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Department Overview The Market Data Analytics Team is part of the Traded Risk Management (TRM) department, supporting a wide area of businesses within Financial Markets and Group Treasury. The team is responsible for all aspects of market data used by the TRM department including market risk, product control, and counterparty credit risk. ING is looking for a Senior Market Data Analyst/ Business Analyst to join the Market Data Analytics Team (MDAT) supporting a team focused on the management of market data sourcing, transformations, models, and proxies, as well as the development of dashboard and data analytics and reporting tools, forming a market data centre of excellence within TRM. We are looking for a candidate who has proven hands-on experience in managing projects, analysing, and visualising large sets of market data, as well as a background in Market Risk and some derivatives pricing knowledge. Main Duties and Responsibilities of Role: Developing and maintaining derived market data and proxy models for multiple asset classes Conducting analysis on large data sets, processes, and technology systems Coordinating and implementing market data used in market risk-related internal initiatives as well as upcoming regulatory changes and strategic market data programmes Being a point of contact to resolve market data queries from our stakeholders including Trading, Risk and Model Validation Collaborating with the global team across the full market data lifecycle including requirements, architecture, implementation, testing, and release management Working closely with the TRM teams to understand and deliver on their market data requirements Co-ordinating agile projects with IT developers and system support teams to develop and maintain high market data quality standards on behalf of TRM Working closely with Model Validation to close out market data related findings Daily market data validation & reporting, defined by the Market Data Replacement & Proxy Policy Candidate Profile Qualification/Education Essential: Graduate (at least UK 2:1 degree) in a quantitative subject (i.e. Mathematics, Computer science, Physics, Chemistry) Economics/Finance degrees considered with a quantitative focus Desirable: Professional qualification (e.g., PRM, FRM, CQF) Experience/Knowledge Essential: Statistical and mathematical background Experience in dealing with large market data sets and associated technologies Experience writing in Python to build solutions particularly with large datasets SQL experience Good quantitative level of experience with several asset classes, their risks and pricing Strong level of understanding of quantification of market risk metrics (VaR, HVaR, IRC, etc.) and market risk capital requirements Desirable: Experience with and keen interest in financial markets relevant policies, guidelines and regulations Understanding of regulatory frameworks as applied internally Closing out model validation and audit findings Azure DevOps and Git version control Experience with systems such as Summit, Murex, Bloomberg, Superset DAP, Reuters, ActivePivot is also a plus Personal Competencies Essential: Strong quantitative problem-solving skills (this will be tested at interview) Skills which ideally included managing direct reports in a previous role Strong communication skills: Position involves regular interaction with colleagues in varying degrees of seniority and understanding of new rules and processes. Candidate should be able to adapt communications to target audiences ranging from senior executives to junior colleagues involved/impacted by new rules and processes Self-starter, proactive, results orientated and flexible, can adjust quickly to new circumstances Must be capable of working and delivering using initiative and time very efficiently under tight timelines Team player with a mindset of empowering others Delivery focused Hands-on approach with good analytical skills Good verbal and written communication skills Fluent in English

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