Data Scientist

Key Skills:

Roles & Responsibilities:

• Develop and implement NLP models using frameworks such as spaCy, NLTK, and Hugging Face Transformers.
• Utilize large language models (LLMs) and embedding techniques for various data science applications.
• Conduct text classification, summarization, topic modeling, named entity recognition, and intent detection.
• Deploy machine learning models in production using orchestration tools like Airflow and MLflow.
• Collaborate in cloud environments, preferably Azure, and utilize tools such as Docker and Kubernetes (AKS).
• Work with data science libraries in Python, including SciPy, NumPy, TensorFlow, and SciKit-Learn.
• Build data science models for user-facing applications, including recommendation systems.
• Integrate with REST APIs and handle streaming datasets.
• Understand and work with graph data using Neo4j and RDBMS data structures, including Azure Tables and Blob storage.
• Implement CI/CD processes using Git for cloud configurations and standard code repositories.

Experience Required:

• 5-8 years of experience in developing and deploying NLP models and machine learning solutions.
• Proven hands-on experience with Python, NLP libraries, and cloud platforms like Azure.
• Strong background in model deployment, orchestration tools, and working with large-scale datasets.
• Practical experience integrating models with APIs and managing production environments using CI/CD tools.

Education: