Senior Data Scientist
On-site · Beijing, Beijing, China
Job Summary
Senior Data Scientist role focusing on building an industry-leading data management and analytics framework for financial data. Own product vision for data acquisition, cleaning, transformation, and workflows; support end-to-end AI/ML lifecycle including problem definition, design, deployment, and continuous improvement. Define optimized analytics workflows for financial data pipelines, integrate multiple tools into a cohesive platform, and translate business data needs into platform strategy. Lead collaboration with engineers and cross-functional teams, communicate progress to stakeholders, stay current with emerging technologies, and deploy production-grade AI models with performance improvements. Required expertise includes NLP, large language models, prompt engineering, RAG, AWS/Azure, Python, ML/DL libraries, data processing of structured to unstructured data, and strong communication skills for leadership interactions. Education and experience align with a Master’s degree in Statistics/Math/CS with DS focus and 6–8 years in data science or analytics, with hands-on capabilities in model development, deployment, data wrangling, and cloud-based data platforms. This role is embedded in London Stock Exchange Group’s Data & Analytics ecosystem and requires collaboration with senior stakeholders across global teams.
Required Qualifications
- Master’s degree in Statistics, Mathematics, or Computer Science with a Data Science certification, or an Engineering degree specializing in Data Science and Artificial Intelligence
- 6–8 years of experience in data science, analytics, or statistical modelling roles
- Strong foundation in data analytics, NLP, predictive modelling, LLMs, and RAG workflows
- Proficiency in Python and core ML/DL libraries (TensorFlow, PyTorch, Scikit‐learn)
- Experience with Git‐based version control and CI/CD pipelines (GitLab/GitHub runners)
- Strong understanding of relational databases, large‐scale data processing, and statistical programming
- Hands‐on experience with AWS and/or Azure and cloud platforms
- Hands‐on experience with data management tools and data processing pipelines
- Excellent communication and presentation skills for technical and business audiences
- Experience with web crawling and scraping, entity identification/extraction, and processing unstructured data
- Familiarity with MLOps principles
- Experience with prompt engineering and retrieval-augmented generation (RAG)
- Experience deploying AI models in production
- Ability to simplify complex technical concepts for broad audiences
- Ability to collaborate with cross-functional teams to define requirements and roadmaps
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