AVP - Quantitative Analytics - Investment Bank

Role Overview :

QA Modelling Systems team is responsible for model implementation of capital (Basel), impairment (IFRS9), and stress testing (CCAR, PRA, EBA) models. QAMS focus on the delivery of model implementation and model frameworks and their integration into production. This involves design and implementation in Python, C++ and R with delivery of associated tooling, quality assurance and testing.

Purpose of role:

- Strong passion for automation of processes in a production environment in an efficient and optimised manner utilising Python or any other analytical tools.

- Technical analysis, design, coding, support, maintenance and testing of components/models within the Python environment

- Support BUK model developers with, model design, integration and on-boarding of their models into Python and IT infrastructure, ensuring models are delivered based on the best possible implemented in a full production environment with full controls adhering to QA policy and standards.

- Support delivery of tools and integration of models using modern technologies such as Python and R programming languages

- Support IT group to on-board data and models into production environment

Key Requirements : 

- Responsibility for the implementation of models through a full Software Development Life Cycle (SDLC) utilizing Python & DevOps tools for automated release management.

- Responsibility for the delivery of fully automated, optimised and tested implementations within the Python environment for the production team to run.

- Work with model developer, data and production teams to support development, delivery and integration of models into IT infrastructure

- Advanced Python skills and track record of developing efficient, optimised, automated and dynamic production processes using DevOps tools like Jira/GitHub/TeamCity/Jenkins/Nexus.

- Advanced Programming in SQL, R, Java, C++ or Scala an advantage.

- Fully understand Software Development Life Cycle (SDLC) and DevOps tools for automated release management.

- Can document technical aspects to a high standard (Functional/Technical Specifications/process flows).

- Can create and execute test strategies and document to a high standard.

Good to have Skills : 

- Masters/PhD Degree in Computer Science, Math or Statistics

- Knowledge of Big Data platforms such as HADOOP and its eco-system

- Knowledge of credit card and/or banking retail business is strongly preferred

- Good exposure to statistical model development - familiarity with Consumer or Wholesale Credit risk modelling experience.

- Supported or working on stress testing across Risk, Treasury or Finance