VP/AVP, Machine Learning Engineer (AI Industrialization), Group Consumer Banking and Big Data Analytics Technology, Technology & Operations
Group Technology and Operations (T&O) enables and empowers the bank with an efficient, nimble and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability and innovation. In Group T&O, we manage the majority of the Bank's operational processes and inspire to delight our business partners through our multiple banking delivery channels. Purpose
To build and improve machine learning and analytics platform. Work with data scientists to create, optimize and productionize of machine learning models for various business units within the organization. Keep innovating and optimizing data and machine learning workflow to enable data-driven business activities at large scale. Responsibilities
Build and improve machine learning and analytics platform.
Work with data scientists to build end-to-end machine learning and analytics solution to solve business challenges.
- Apply cutting edge technologies and tool chain in big data and machine learning to build machine learning and analytics platform.
- Keep innovating and optimizing the machine learning workflow, from data exploration, model experimentation/prototyping to production.
- Provide engineering solution and framework to support machine learning and data-driven business activities at large scale.
- Perform R&D on new technologies and solutions to improve accessibility, scalability, efficiency and us abilities of machine learning and analytics platform.
Establish, apply and maintain best practices and principles of machine learning engineering.
- Turn advanced machine learning models created by data scientists into end-to-end production grade system.
- Build analytics platform components to support data collection, exploratory, and integration from various sources being data API, RDBMS, or big data platform.
- Optimize efficiency of machine learning algorithm by applying state-of-the-art technologies, i.e. distributed computing, concurrent programming, or GPU parallel computing.
- Study and evaluate the state-of-the-art technologies, tools, and frameworks of machine learning engineering.
- Contribute in creation of blueprint and reference architecture for various machine learning use cases.
- Support the organization in transformation towards a data driven business culture.
- Machine learning frameworks such as TensorFlow or Keras
- Knowledge of Hadoop, Spark or any other distributed computing systems
- Advanced math skills (linear algebra, Bayesian statistics, group theory)
- Knowledge of Machine Learning Algorithms and Libraries
- Working with version control system
- Understanding of distributed eco system
- Spark Core, Spark-SQL, Scala-Programming and Streaming datasets in Big Data platform
- Programming experience in Python, R, Scala or Java
- Excellent understanding of technology life cycles and the concepts and practices required to build big data solutions
We offer a competitive salary and benefits package and the professional advantages of a dynamic environment that supports your development and recognises your achievements.