Assistant Vice President - Machine Learning (ML) Engineering

Some careers have more impact than others.

If you’re looking for a career where you can make a real impression, join HSBC and discover how valued you’ll be.

HSBC is one of the largest banking and financial services organizations in the world, with operations in 62 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realize their ambitions. 

We are currently seeking an experienced professional to join our team in the role of Assistant Vice President – Machine Learning (ML) Engineering

Principal Responsibilities

• Act as a technical and data Subject Matter Expert (SME) for the wider teams
• Ensure the data quality is up to the set standards and be able to design and implement a robust data quality framework.
• Defining validation strategies and establishing a process to ensure acceptable data quality criteria are achieved.
• Responsible for maintaining the infrastructure that supports the models and algorithms that power the products of the team, Monitoring the performance of these systems, identifying ways to improve model performance, investigating issues when it arise.
• Monitor the performance of models, and need to be able to troubleshoot any errors or bugs that may occur.
• Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market.
• Define robust data models for both structured and unstructured data.
• Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics. 
• Manage Data management order book in consultation with Contact Centre Heads and Transformation Leads, assess skill / resource requirements, evaluate data and infrastructure requirements, track progress against plan and provide regular updates to the Working Group.
• Proactively identify process gaps and share ideas to close the gaps and actively work towards closing the gaps.