AVP, Quant Data Analyst (SQL, R, Python)

My client a leading Investment Bank are looking to recruit a Data Analyst with strong quantitative and analytical skills to join the Quantitative Analytics group.The team is responsible for the research, development and implementation of cutting-edge, market leading quantitative models across all asset classes (Interest Rates, Credit, Equity, Foreign Exchange, Commodities, Emerging Markets and Counterparty Risk) and risk types (market, credit, counterparty).QA Wholesale Credit Risk develop models for capital (Basel), impairment (IAS39/37, IFRS9), and stress testing (CCAR, PRA, EBA). Model outputs are utilised across a range of risk metrics, including RWA, pricing, Economic Capital, and for credit sanctioning. The model scope covers the Corporate and Investment Bank (CIB) within the company.Role Purpose:* Enable effective use of data from across BI by QA WCR through support and development of the Wholesale Datamart.* Thorough and deep analysis for modelling data, and preparation and documentation of data for model development. Key Accountabilities:* Validate data provided to QA, including implementation of data validation code.* Document QA data processing tests and data requirements for IT.* Process data provided to QA, e.g. ratio transformations and merging data tables.* Support implementation runs; this includes responding to questions on data transformations as well as initial questions on results before passing on to others in the team Level of accountability. Required Skills & Experience:* Strong stakeholder management skills, with experience from complex projects.* Good project and people management skills; ability to motivate team and deliver within tight deadlines.* Strong quantitative and analytical skills; degree(s) in a quantitative discipline such as Computer Science, Math, Engineering.* Strong technical skills: SQL (Teradata, SQL Server) (essential) R or Python (preferred)* Significant experience with data management / architecture / storage / reporting within a financial institution.* Experience analysing data and model calculation outputs.* Good documentation and communication skills.* Domain expertise in Wholesale PD, LGD, EAD. Candidate Profile: * Ability to quickly adapt to new environments & systems.* A keen eye for detail.* Self-starter: motivated and disciplined.* Able to work in isolation and within a team environment as required.