Senior Data Scientist

4 weeks ago


Singapore DBS Bank Limited Full time
About the Role

As a Senior Data Scientist at DBS Bank Limited, you will play a pivotal role in advancing data-driven strategies to drive business impact and enhance customer experiences. You will lead complex data science projects, provide best-in-class analytics and AI / ML solutions that drive decision-making across T&O, while ensuring alignment with DBS' AI industrialization agenda.

Key Responsibilities:
  • Lead the development and execution of AI / ML and generative AI strategies and capabilities, aligning with the bank's AI industrialization agenda.
  • Design, develop and deploy advanced machine learning models and algorithms to support T&O's strategic priorities, including establishing scalable data science pipelines.
  • Ensure robust model governance, including performance monitoring, validation, and re-calibration, in line with governance standards and best practices.
  • Support the implementation of AI industrialization in T&O and drive reduced effort for end-to-end deployment of models by supporting the creation and usage of reusable components across the AI / ML Lifecycle.
  • Collaborate with different business stakeholders across Operations, Data Chapters and Technology to define and prioritize AI / ML initiatives that drive impactful business outcomes.
  • Engage with senior leadership and business heads to identify opportunities where data science can deliver significant value.
  • Stay abreast of industry trends, emerging technologies, and best practices in data science and drive knowledge sharing across AI / ML use cases in T&O and across Data Chapters.

Requirements:
  • PhD or Master's or equivalent degree in Computer Science / Engineering / Mathematics, or other related fields, preferably in the areas of Machine Learning, Data Mining, Deep Learning, or equivalent quantitative fields.
  • Minimum 10 years of data science experience in industry (ideally banking, ecommerce, telecoms, retail, or technology firms) and/or academia with demonstrated track record of innovative research and insight generation and implementation of insights into tools/processes delivering front-end business outcomes.
  • Minimum 5 years of experience working with large datasets (including structured, semi-structured and unstructured data), building, and implementing various machine learning models or applications.
  • Excellent modelling background including but not limited to classification, clustering, recommender systems, deep learning, reinforcement learning, natural language processing etc.
  • Proven track record of deploying machine learning solutions into production environments, integrating them into operations, and implementing continuous model performance monitoring.
  • Familiar with software development best practices and tools.
  • Experience in implementing generative AI models is a plus.
  • Strong communication, interpersonal and stakeholder management skills.


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