Data Scientist - Azure AI & Data Platform

About the Role:

We are seeking a highly motivated Data Scientist with strong expertise in designing and implementing AI and data-driven solutions on the Microsoft Azure platform. You will play a key role in solving complex business challenges using machine learning, advanced analytics, and cloud-native technologies.

Key Responsibilities:

• Design and implement AI/ML models and advanced data analytics solutions tailored to business requirements.
• Build end-to-end data pipelines and machine learning workflows using Azure Machine Learning, Azure Synapse, Azure Data Factory, and related services.
• Collaborate with data engineers, product owners, and business stakeholders to identify AI use cases and translate them into technical solutions.
• Deploy, monitor, and retrain models in production environments using MLOps best practices on Azure.
• Conduct exploratory data analysis (EDA), feature engineering, and model optimization.
• Ensure data security, compliance, and governance standards are met within the Azure environment.
• Communicate findings and insights through dashboards, reports, and visualizations using Power BI or equivalent tools.

Required Skills & Qualifications:

• 4–5 years of experience as a Data Scientist working on AI/ML use cases.
• Strong hands-on experience with Microsoft Azure services:
• Azure Machine Learning
• Azure Synapse Analytics
• Azure Data Factory
• Azure Blob/Data Lake Storage
• Azure DevOps / MLOps
• Proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience in building and deploying models for classification, regression, forecasting, NLP, or computer vision.
• Solid understanding of data wrangling, data preprocessing, and model evaluation techniques.
• Strong problem-solving and communication skills.

Preferred Qualifications:

• Microsoft Certified: Azure Data Scientist Associate (DP-100) or equivalent.
• Experience with Power BI for data visualization and storytelling.
• Exposure to data governance frameworks and responsible AI practices.