Senior Analyst, Data - Risk Management (CIB)

To source, analyse, provision and report data to internal clients, timeously, in the necessary format and of outstanding quality, to contribute towards the creation / enhancement of CIBs Credit Risk models and programmes, and in subsequent appraisal of results, to quantify and manage credit risks and optimise risk decision-making associated with Counterparty, Transactional, Country/Sovereign, Industry/Sector specific risk.Key Responsibilities/Accountabilities:Business needs analysis Receive requests for data, engage and collaborate with internal and / or external stakeholders to understand business data requirements and proactively interrogate stakeholders to ensure that credit risk data are delivered in an appropriate format and to the desired specifications.Data sourcing Identify and evaluate alternate, available and relevant data sources to ensure reliability, validity and simple, efficient access to appropriate source data. Locate and remove duplicate sources of data and download and store required data resources in a chronological structure.  Where required, work with other analysts and data engineers on quality assurance of source data and systems.Data cleaning Identify and resolve any ad hoc and / or persistent data quality and integrity issues by conducting both routine and ad-hoc data cleaning and testing, to facilitate the generation of aggregate and up-to-date risk data in a timely manner while also meeting the principles relating to accuracy, integrity, completeness and adaptability. Data processing Perform data pre-processing (i.e. data manipulation, transformation, normalisation, standardisation, visualisation and derivation of new variables/features), as applicable to developing specific algorithms or models. Build rules to transform the data into normalised data and / or report formats, depending on the needs of Model Development. Compile, sort and organises data in preparation for subsequent analysis.​​​​​​​Data analysis Discover and apply insights from big data sets of structured, semi-structured, and unstructured data. Apply data mining techniques, perform statistical analysis on large data sets and validate analysis using appropriate techniques (applying test data sets, A/B testing, scenario modelling, etc.).​​​​​​​Stakeholder engagement Form productive networks with internal and external stakeholders. Collaborate to develop / enhance existing credit risk predictive models to meet specific business needs. Work with data analysis colleagues to review, approve, produce or update system or object data models and correlate these with CIB models. Work with database design or administration teams to translate object and data models into appropriate database schemas within design constraints.  ​​​​​​​Quality assurance Ensure all technical solutions are delivered within continuous integration standards and agreed timelines.  Quality assure work completed by junior colleagues, including code and business rules developed, supporting documents and test plans. Review work done by data analysts to assure compliance with standards, methods and tools used in the bank for application development. ​​​​​​​ReportingLead, develop and generate routine and ad-hoc reports, dashboards and risk data fact sheets in line with business requirements (i.e. in the required formats and with the relevant visualizations and commentary). Prepare interpretation of finding into clear, actionable, and timely insights and present these to internal and/or external clients (e.g. Credit Risk, Model Development and External Agencies).​​​​​​​Policies, procedures, systems standards and toolsDevelop and document policies, procedures, governance guidelines and SLAs. Comply with all applicable policies, standards, systems, processes, and procedures (including Risk Data Aggregation and Risk Reporting (RDARR) standards and technical policies and the BCBS 239 (Basel Committee on Banking Supervision) data governance standards) so that all relevant risk and governance requirements are fulfilled while consistently delivering quality products and services.  ​​​​​​​Data stewardship and risk management Drive consistent standards for data management and analysis tools and techniques and ensure compliance requirements are met for both structured and unstructured data. Ensure that strong controls are in place to deliver data that is fit for purpose within the business. Participate in disaster mitigation and recovery plans for solutions and databases supported.