AVP/Senior Associate, Machine Learning Engineer, COO-office, Institutional Banking Group
The Institutional Banking Group's (IBG) Data Centre of Excellence (DCOE) is committed to building a data-driven organisation and maximising the key data capabilities to transform how IBG does business. Data impacts IBG's business every day, and a culture of relentlessly using data and business intelligence will enable IBG achieve exponential growth. Job Purpose
The Machine Learning Engineer will apply data analytics (including descriptive and prescriptive analytics), machine learning and software engineering skills in various data science projects, with ownership of over the entire data analytics life cycle. Responsibilities
- Discuss with business stakeholders to understand the business problems.
- Propose, prove, and own suitable analytics solutions.
- Develop and execute on project plans, including schedules, specifications, risks, and contingency plans.
- Apply cutting edge technologies and tools in big data to build and manage data pipelines.
- Develop and implement machine learning algorithms and build production-grade end-to-end analytics solutions together with cross-functional teams including business, data science, technology, and production teams.
- Monitor model performance and maintain the analytics models and pipelines.
- Bachelor's or master's degree in Computer Science, Business Analytics, or related fields.
- 3-8 years of experience in software application development involving high volume of data, and in leveraging advanced analytics and machine learning to achieve business impact.
- Excellent programming skills in Python, SQL, shell script.
- Familiar with software development and productivity tools such as VS Code, PyCharm, Jupyter, Jira, Git, Confluence.
- Strong in problem-solving, being resourceful with end-to-end critical thinking to find out solutions even in unfamiliar scenarios.
- Team player with good communication and project management skills.