Assistant Vice President - Decision Science

Job Description

Some careers have more impact than others. We are currently seeking an experienced professional to join our team in the role of Assistant Vice President - Decision Science Principal responsibilities Lead the model development projects and coordinate with stakeholders as well. Functionally drive the development methodologies and design the validation framework Engage with credit and businesses to manage model risk. Attention to time schedule and resource planning, participate to panel meetings and discussion with business experts, write good quality and comprehensive documentation. Maintain HSBC internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators. Enhanced data processes to allow more efficient model validation and development for SME and Wholesale data marts Develop, test and write highly complex application programs, queries and profiles aligned to business goals Identification of data sources and obtain appropriate access Formal model development documentation for sign off Help identifying areas which require data remediation and proactively engage with internal stakeholder to address them. Support and lead the preparation of data for model build, enhancement and deployment of SME and credit risk models, as directed. Lead a team of analysts and guide them with day to day activities including their performance management Requirements Masters / Ph.D in any numeric discipline :- Statistics / Economics / Engineering (or B-tech with relevance experience)/ Mathematics Around 6-10 years of professional experience in financial services risk scorecard models development experience or regulatory risk model development (PD, EAD, LGD) Candidates with entire model development experience preferably with model documentation and review. Understanding of regulatory implications and relevance, preferably worked in a bank Understanding of commercial banking and related products Knowledge of data-engineering and industry coding standards would be a plus Highly comfortable with solving unstructured business and technical problems Excellent written english and verbal communication skills Hands-on statistical knowledge with scorecard /econometric model development capability Strong programming skills in Python with ability to work on large datasets is a must Proficiency in PySpark and Pydash is desired Able to progress multiple tasks at the same time Enthusiastic, displaying energy, drive and stamina Strong knowledge of wholesale credit business and wholesale credit products as well as Basel framework