Vice President - Model Development & Execution - Advanced Python + DevOps Tools (10-15 yrs) | E Consultant | Noida - Vasitum

Vice President - Model Development & Execution - Advanced Python + DevOps Tools (10-15 yrs)

e Consultant
Posted: 9 months ago
Job Views: 2
Python ,
Big Data ,
Statistics ,
Statistical Modeling ,
Machine Learning ,
Python ,
Big Data ,
Statistics ,
Statistical Modeling ,
Machine Learning ,
Job Description

The role will require a strong quant development experience with core responsibilities:

- Excellent skills programming in python/C++/Java with extensive experience working in delivering software and hands on experience working with modelling team

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

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

- Delivery of model execution service to risk, finance and treasury teams that will cater to the business and regulatory modelling needs

- Support building and adoption of DevOps tools infrastructure across QA MDE team

- Support ongoing improvements and automation of the model development lifecycle across QA MDE, QA model development, IVU, QA Model monitoring and IT teams

- Work with QA MDE leadership to define standards and best practices for QA MDE team

- Upskilling & Cross-skilling of team on various open source tools and DevOps technologies that QA offers, such as Python, R, Java, Jira, Git, TeamCity and Nexus etc

- Apply innovative thinking and complex problem solving skills to support the QA teams, risk, finance, treasury business & technology to deliver strategic objectives

- Work with global QA teams to define strategy and deliver models with adotpion of DevOps, process improvement, automations/agile and software development practices

- Work with QA MDE leadership team in NYK/LDN & NOIDA to define strategy & execution for Cloud journey & adoption in QA

What will you be doing?

- 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 with Python environment for the production team to run.

- Responsibility for the delivery of fully tested and optimized code through full SDLC with DevOps tools.

- Work within the QA MDE teams (based globally across UK, US and India) on model development focusing on end to end model delivery

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

What we- re looking for:

- Bachelors Degree in Computer Science from a Top School, or a Masters Degree in another technical discipline (Physics, Engineering, Maths) with relevant experience

- Advanced Python Programming and knowledge of Java/C++ coding.

- Experience in model implementation using DevOps tools like TeamCity, Jira, BitBucket and Nexus etc

- Excellent People, Project and stakeholder management experience.

- Experience in financial institution delivering models, supporting model development, implementation and productionisation within credit wholesale, consumer, finance or treasury.

- Able to deliver to tight deadlines on quantitative projects, and manage the end to end process of model execution delivery.

- Supported or working on CCAR, IFRS9, IRRBB, stress testing across Risk, Treasury or Finance

- Data science background

Skills that will help you in the role:

- 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.

- Stress testing and balance sheet forecasting experience

- Machine learning background