Geylang - Senior Data Scientist (Banking / Financial Services)
An established financial institution is seeking a senior Data Science Expert to lead the development and implementation of advanced data-driven solutions within its capital markets technology team. This role will be pivotal in driving innovation using AI and machine learning to enhance trading, risk, and post-trade operations.
Responsibilities- Design, build, and maintain intelligent systems that support trading, investment, and risk processes across the capital markets lifecycle
- Apply deep learning and machine learning techniques to streamline complex workflows and deliver predictive insights for business users
- Develop and deploy generative AI solutions to simulate market conditions, generate synthetic financial data, automate post-trade analysis, and enrich stakeholder interactions
- Collaborate with trading desks, quantitative analysts, and functional teams to shape AI use cases that align with real-world business problems
- Build scalable AI components and services that integrate into the broader IT ecosystem with a product-oriented mindset
- Take ownership of architecture, code quality, deployment strategies, and continuous improvement across models and data pipelines
- Serve as the subject matter expert in AI technologies, bringing in innovation while ensuring compliance and ethical use of data and models
- 10+ years of experience in enterprise-level IT, preferably within capital markets, financial services, or large-scale trading systems
- Strong foundation in machine learning, deep learning, generative AI, and operationalizing models (MLOps/LLMOps)
- Practical experience with model development using frameworks like TensorFlow, PyTorch, or Scikit-learn
- Familiarity with modern GenAI stacks, including LLMs, retrieval-augmented generation (RAG), and public cloud deployment (AWS, Azure, etc.)
- Proficient in Python (required), and exposure to .NET or Java is a plus
- Experience deploying solutions in cloud-native environments using GitLab CI/CD, Kubernetes, and containerized workflows
- Deep understanding of data preparation, ethics in AI, and how to generate and optimize embeddings for production-grade GenAI models
Those who are keen for the role and would like to discuss the opportunity further, please click "Apply Now" or email Kin Long at kfok@morganmckinley.com with your updated CV.
Only shortlisted candidates will be responded to, therefore if you do not receive a response within 14 days, please accept this as notification that you have not been shortlisted.
Kin Long Fok
Morgan McKinley Pte Ltd
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