Roles & Responsibilities :

Machine Learning & Data Science:

Develop and implement advanced statistical models, predictive analytics, and optimization frameworks.
Research, develop, and apply ML, Deep Learning, and AI techniques on large datasets.
Conduct exploratory data analysis (EDA) and apply feature engineering techniques.
Optimize and tune ML models for performance, scalability, and accuracy.

Large Language Models (LLMs) & NLP:

Fine-tune and customize LLMs (GPT, Claude, Gemini, etc.) for enterprise use cases.
Implement Retrieval Augmented Generation (RAG) pipelines for chatbots and knowledge retrieval.
Work with vector databases for semantic search.
Deploy LLM-powered applications for document summarization, sentiment analysis, and automation.

AI & Data-Driven Business Insights:

Translate complex AI/ML models into actionable business insights.
Partner with stakeholders to define data requirements and ensure the right data is captured.
Develop proof-of-concept solutions demonstrating AI and ML capabilities.

Deployment & MLOps:

Deploy AI/ML models using cloud technologies (Azure, AWS, GCP).
Work with Docker, Kubernetes, and CI/CD pipelines for scalable ML deployment.

Continuous Learning & Innovation:

Stay updated with the latest trends in AI, LLMs, GenAI, and cloud-based ML platforms.

Qualifications & Skills

Technical Skills:

Strong experience in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras, SciPy).
Hands-on expertise with LLMs, NLP techniques, and vector search (LangChain, Hugging Face).
Solid understanding of statistics, probability, and data science methodologies.
Experience with data pipelines (ETL, Spark, Hadoop, SQL, NoSQL, Data Lakes, Databricks).
Knowledge of Cloud AI services (Azure ML, GCP Vertex AI).
Strong software engineering principles with experience in Jupyter Notebooks, API development, and workflow automation.
Solid understanding of Cloud Technologies (ideally Microsoft Azure) and SQL are beneficial

Soft Skills:

Data Scientist

Job Description