Lead Data Scientist
CNY 435K-510K (estimate) Senior-level Full Time
Tasks
- Apply model evaluation tuning and scaling
- Assess third party AI tools for build versus buy
- Build production grade AI models
- Build scalable data pipelines with data engineering
- Define AI ML success criteria and evaluation frameworks
- Define data acquisition and transformation workflows
- Deliver end-to-end data science projects
- Deploy ML and AI solutions on cloud platforms
- Deploy multimodal models for text and media
- Design financial analytics pipelines
- Develop retrieval-augmented generation systems
- Ensure responsible AI governance and compliance
- Generate synthetic data for model robustness
- Implement AI agents and human AI collaboration
- Implement LLMOps and MLOps workflows
- Improve monitoring observability and model lifecycle management
- Lead experimentation and adoption of emerging AI techniques
- Own large scale ML projects
- Perform web scraping crawling and preprocessing
- Process structured semi structured and unstructured data
- Provide technical architecture guidance
- Set up CI/CD pipelines
- Translate business requirements into technical specifications
Perks/Benefits
Skills/Tech-stack
AI Agents | AWS | Azure | CI/CD | Cloud Computing | Data Preprocessing | Data extraction | Data postprocessing | Deep learning | Entity recognition | Generative AI | Git | Human-in-the-loop | LLMOps | Langchain | Language Models | Language Processing | Large Language Models | Llamaindex | MLOps | Machine Learning | Model Evaluation | Model Tuning | Monitoring | Multimodal AI | Natural Language | Natural Language Processing | Observability | Python | R | Responsible AI | Retrieval-Augmented Generation | SQL | Synthetic data | The Loop | Vector Databases | Web Scraping
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Data Scientist | Engineer | Lead | Lead Data | Lead Data Scientist | Learning Engineer | Machine Learning Engineer | Scientist
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