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OCBC

Data Scientist, AI Lab (AM/MGR)

Department
Engineering
Job Type / Location
onsite
Experience Required
2+ years
Posted On

About the Role

Working within the Group Data Science, 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 a variety of problems from traditional AI and Machine learning to Generative AI problems when needed.

Responsibilities

  • Work with business leaders across OCBC Group to identify opportunities for leveraging big data and Data Science to drive value for our customers and business.
  • Develop and maintain machine learning/deep learning models to achieve the desired business outcomes – such as State of the Art Reinforcement learning system or RAG.
  • Develop and maintain models in production. Set up controls and monitoring for the models.
  • Use MLOps processes and tools to monitor and refine Production model performance and accuracy.

Job Qualifications

Specific Knowledge

  • 2 years+ of experience manipulating data sets and building statistical models, ideally with a Master’s or PhD in Statistics, Mathematics, Computer Science or other quantitative field.
  • Strong programming experience, with solid understanding of software engineering design patterns and best practices.
  • Experience with big data technologies such as Hadoop, Trino, and Spark.
  • Some experience in the use of CI/CD and DevOps tools such as Jira, Jenkins, GIT/Bitbucket.
  • You have a passion for AI and ML, and you want to learn more everyday.

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.

View Assessment Process

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