Senior Manager – Data Scientist
Tasks
- Build RAG pipelines
- Build multi-agent systems
- Conduct architecture reviews
- Conduct code reviews
- Conduct cost/benefit analysis
- Create solution product design
- Deploy on AWS
- Deploy on Azure
- Explore AI trends for HR use cases
- Identify HR business problems
- Lead end-to-end AI implementation
- Lead innovation ideation with SMEs
- Mentor data scientists and AI engineers
- Orchestrate LLM workflows
- Oversee solution development, testing, deployment
- Prioritize AI use cases
- Provide executive updates
- Translate business requirements into technical specifications
Perks/Benefits
Skills/Tech-stack
AWS | AWS SageMaker | Agent systems | Agentic AI | Azure | Azure ML | BERT | Chain-of-Thought | Cloud | Clustering | Convolutional Neural Networks | Deep learning | Fine Tuning | GPT | GenAI | Google Vertex | Google Vertex AI | Keras | LLM Evaluation | LLM orchestration | Language Processing | LoRA | Logistic Regression | Long Short-Term Memory | Machine Learning | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | Neural Networks | PEFT | Pandas | Prompt engineering | PyTorch | Python | RAG | Random Forest | React | Recurrent Neural Networks | Retrieval-Augmented Generation | SQL | Scikit-learn | Short Term Memory | Spark | Support Vector Machine | TensorFlow | Transformers | Vertex AI | XGBoost
Education
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