Senior Data Scientist
4 weeks ago
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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