Data Scientist

Key Responsibilities:

Develop, implement, and maintain machine learning models and algorithms using Python, PyTorch, and TensorFlow.

Leverage BERT, Transformers, and other NLP models to analyze and interpret complex data.

Utilize large language models (LLMs) for various applications, including text generation, summarization, and sentiment analysis.

Build and deploy data applications using Streamlit for interactive visualization and data exploration.

Work with Amazon SageMaker to train, tune, and deploy machine learning models at scale.

Collaborate with cross-functional teams to gather requirements and deliver data-driven insights.

Perform data cleaning, preprocessing, and feature engineering to prepare data for model training.

Implement retrieval-augmented generation (RAG) techniques to enhance model performance.

Optional: Integrate with Pinecone for scalable vector search and similarity search.

Optional: Collaborate with the Hugging Face community for model fine-tuning and deployment.

Qualifications:

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.

Minimum of 3 years of experience as a Data Scientist or in a similar role.

Strong programming skills in Python and experience with libraries such as Pandas, NumPy, and Scikit-learn.

Proficiency with deep learning frameworks such as PyTorch and TensorFlow.

Hands-on experience with NLP models like BERT and Transformers.

Familiarity with large language models (LLMs) and their applications.

Experience with AWS SageMaker for model training and deployment.

Knowledge of Streamlit for creating data-driven applications.

Excellent problem-solving skills and the ability to work independently and in a team environment.

Strong communication skills to convey complex technical concepts to non-technical stakeholders.