Data Scientist

Key Responsibilities:

Collaborate with cross-functional teams to identify, analyze, and interpret complex datasets to develop actionable insights and drive data-driven decision-making.
Design, develop, and implement Generative AI solutions leveraging AWS Bedrock, Azure OpenAI, Azure Machine Learning, and Cognitive Services.
Utilize Azure Document Intelligence to extract and process structured and unstructured data from diverse document sources.
Build and optimize data pipelines for processing and analyzing large-scale datasets efficiently.
Implement Agentic AI techniques to develop intelligent, autonomous systems that can make decisions and take actions.
Research, evaluate, and recommend embedding models, language models, and generative models for diverse business use cases.
Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed.
Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones.
Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth.
Ensure model explainability, fairness, and compliance with responsible AI principles.
Stay up to date with the latest advancements in AI, ML, and data science, and apply best practices to enhance business operations.

Minimum Qualifications / Skills:

Hands on experience in data science, machine learning, AI applications, generative AI prompt engineering, creating custom models.
Strong proficiency in Python, TensorFlow, PyTorch, PySpark, Scikit-learn, and MLflow.
Hands-on experience with Azure AI services (Azure OpenAI, Azure Document Intelligence, Azure Machine Learning, Azure Synapse, and Azure Data Factory, Data Bricks, RAG pipeline).