Data Scientist
Tasks
- Build RAG pipelines for question answering and document understanding
- Build supervised and unsupervised machine learning models
- Communicate insights using data visualization
- Create and optimize reusable modeling pipelines
- Design prompt engineering and fine tuning strategies for LLMs
- Develop and deploy language model based machine learning solutions
- Develop deep learning models for NLP and computer vision
- Develop evaluation metrics and studies
- Mine and analyze customer data
- Perform data preprocessing, feature engineering, and exploratory data analysis
- Translate analytics into actionable product recommendations
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agents | Autogen | Azure | Azure OpenAI | BERT | Computer Vision | CoreNLP | ELMo | Entity recognition | FastAPI | Fine Tuning | Flask | GPT | Gensim | Google Cloud | Guardrails | Intent Recognition | Keras | Knowledge graphs | LLM | Langchain | Language Processing | Llamaindex | LoRA | NLTK | Natural Language | Natural Language Processing | OpenAI GPT | OpenNLP | PEFT | Pinecone | Postman | Prompt engineering | PyTorch | Python | QLoRA | Qdrant | Question Answering | R | RAG | Spacy | Swagger | TensorFlow | Text Classification | Text Summarization | Topic Modeling | Transformers | Vector Databases | WordNet | XLNet
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