onsite

Data Science - ED

As a Data Scientist - ED at OCBC, you will work within the Group Data Science team, leveraging large volumes of structured and unstructured data to solve business problems across the OCBC Group. You will focus on AI and Generative AI applications for conversational bots and content generation, leading a Data Science squad to drive value for customers and improve operational efficiencies, risk reduction, and client experiences.

About the role

Overall Role Purpose

Working within the Group Data Science team, you will leverage huge volumes of Structured and Unstructured data to solve real business problems across the OCBC Group.
You will work closely with business to understand their problem statements and transform them into ML and AI challenges when needed.
You will work on AI and Generative AI, assessing, building, and serving AI applications for conversational bots and content generation.

Responsibilities

Work with business leaders across OCBC Group, you will lead a Data Science squad to identify opportunities for leveraging big data, conventional AI and gen AI techniques to drive value for our customers and business.
Particularly for this role, the targeted use cases would fall into improve the banks’ day-to-day operational efficiencies, reducing risks and improving our clients’ customer experiences.
Partner with Data Engineering to source internal & external datasets for analysis.
Develop and maintain machine learning/deep learning models to achieve the desire business outcomes – such as marketing recommendations, fraud detection or credit scoring.
Coordinate with different functional teams to deploy models and smart applications into Production.
Production of complex and large pretrained and fine tune models.
Use MLOps processes and tools to monitor and refine Production model performance and accuracy.

Specific Knowledge

Experience manipulating data sets and building statistical models, with a background in Statistics, Mathematics, Software Engineering, Computer Science or other quantitative field.
Experience leading a team of seasoned Data Scientists with exposure to cross-functional team leadership.
Hands-on programming experience, with solid understanding of AI/software engineering design patterns and best practices. Experience with big data technologies such as Hadoop, Trino and VectorDB (elastic), Ray.
Ideally experience in On-premise distributed Framework for serving and training models.
Ideally experience with large language model fine tuning and distilling.
Experienced in the use of CI/CD and DevOps tools such as Jira, Jenkins, GIT/Bitbucket. Ideally has track record of deploying Machine Learning solutions into Production at scale for AI and GenAI.

Communication & Soft Skills

Ability to execute in a fast-paced environment.
Creativity to see possibilities within the data & translate into compelling stories, decisions and actions for non-technical business users.
Strong communication skills and drive to deliver business benefits in the real-world.
Genuine drive to learn and master new technologies and techniques.

About the role

Overall Role Purpose

Working within the Group Data Science team, you will leverage huge volumes of Structured and Unstructured data to solve real business problems across the OCBC Group.
You will work closely with business to understand their problem statements and transform them into ML and AI challenges when needed.
You will work on AI and Generative AI, assessing, building, and serving AI applications for conversational bots and content generation.

Responsibilities

Work with business leaders across OCBC Group, you will lead a Data Science squad to identify opportunities for leveraging big data, conventional AI and gen AI techniques to drive value for our customers and business.
Particularly for this role, the targeted use cases would fall into improve the banks’ day-to-day operational efficiencies, reducing risks and improving our clients’ customer experiences.
Partner with Data Engineering to source internal & external datasets for analysis.
Develop and maintain machine learning/deep learning models to achieve the desire business outcomes – such as marketing recommendations, fraud detection or credit scoring.
Coordinate with different functional teams to deploy models and smart applications into Production.
Production of complex and large pretrained and fine tune models.
Use MLOps processes and tools to monitor and refine Production model performance and accuracy.

Specific Knowledge

Experience manipulating data sets and building statistical models, with a background in Statistics, Mathematics, Software Engineering, Computer Science or other quantitative field.
Experience leading a team of seasoned Data Scientists with exposure to cross-functional team leadership.
Hands-on programming experience, with solid understanding of AI/software engineering design patterns and best practices. Experience with big data technologies such as Hadoop, Trino and VectorDB (elastic), Ray.
Ideally experience in On-premise distributed Framework for serving and training models.
Ideally experience with large language model fine tuning and distilling.
Experienced in the use of CI/CD and DevOps tools such as Jira, Jenkins, GIT/Bitbucket. Ideally has track record of deploying Machine Learning solutions into Production at scale for AI and GenAI.

Communication & Soft Skills

Ability to execute in a fast-paced environment.
Creativity to see possibilities within the data & translate into compelling stories, decisions and actions for non-technical business users.
Strong communication skills and drive to deliver business benefits in the real-world.
Genuine drive to learn and master new technologies and techniques.