Senior Data Scientist
Tasks
- Apply statistical and analytical techniques
- Balance accuracy explainability cost scalability
- Build and maintain RAG pipelines
- Collaborate on data pipelines and feature engineering
- Communicate technical concepts to non-technical audiences
- Deploy models via APIs and batch processes
- Design, build, deploy machine learning models
- Develop LLM applications
- Document approaches models and learnings
- Enable vector search and retrieval
- Evaluate model performance
- Fine-tune LLMs
- Implement embedding generation
- Integrate with analytics platforms
- Lead data science projects
- Orchestrate model workflows
- Perform prompt engineering
- Support MLOps model deployment and monitoring
- Use and evaluate AI frameworks and libraries
- Use cloud services for training deployment and scaling
- Work with structured and unstructured data
- Write, optimize, and maintain SQL queries
Perks/Benefits
- Cycle to work scheme
- Enhanced parental leave
- Flexible benefits package
- Gym discounts
- Life assurance
- Pension
- Private healthcare
- Regular social events
- Retail discounts
Skills/Tech-stack
AWS | Azure | Bias Mitigation | Cloud platform | Embeddings | Explainable AI | Fine Tuning | Google Cloud | Google Cloud Platform | Graph Databases | Langchain | Language Models | Large Language Models | MLOps | Machine Learning | Model Deployment | Model Evaluation | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | SQL | Scikit-learn | Vector Databases | Vector Search
Education
N/A
Roles
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