Data Scientist
Tasks
- Build and fine-tune language models
- Build reusable modeling pipelines and tools
- Conduct exploratory data analysis and statistical modeling
- Design deep learning architectures for NLP and computer vision
- Develop and deploy machine learning models
- Develop new metrics and studies to quantify product value
- Develop supervised and unsupervised NLP models
- Implement RAG for question answering and document understanding
- Mine and analyze customer data to find product insights
- Perform data collection preprocessing and feature engineering
- Translate analytics into actionable business recommendations
Perks/Benefits
- N/A
Skills/Tech-stack
Agents | Autogen | BERT | Computer Vision | CoreNLP | Data Analysis | Deep learning | ELMo | Entity recognition | Exploratory Data Analysis | Feature Engineering | Fine Tuning | Gensim | Guardrails | Intent Recognition | Keras | Knowledge graphs | Langchain | Language Model | Language Modeling | Language Models | Language Processing | Language model fine-tuning | Large Language Models | Llamaindex | LoRA | Model Fine-tuning | NLTK | Natural Language | Natural Language Processing | OpenNLP | PEFT | Pinecone | Prompt engineering | PyTorch | Python | QLoRA | Qdrant | Question Answering | R | RAG | Spacy | TensorFlow | Text Classification | Text Summarization | Topic Modeling | Transformers | Vector Databases | WordNet | XLNet
Roles
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