Description

Key Skills: Hadoop, Big Data, Python, Pandas, NumPy, Matplotlib, Seaborn, SQL, Data Cleaning, Data Transformation, Data Validation, AI/ML Concepts, Supervised Learning, Unsupervised Learning, Model Metrics, Large Datasets, Apache Spark, Jupyter Notebook, Git, Agile, Azure, AWS

Roles & Responsibilities:

• Analyze, clean, and prepare structured and unstructured data for AI/ML use cases.
• Develop Python-based data analysis scripts and Jupyter notebooks for processing and analysis.
• Perform exploratory data analysis (EDA) and basic feature engineering to derive meaningful insights.
• Conduct data cleaning, transformation, and validation to ensure data quality and consistency.
• Generate reports, dashboards, and visualizations for both business and technical stakeholders.
• Support model evaluation activities through data validation and metric analysis.
• Work with large datasets using SQL and Big Data technologies to identify trends and patterns.
• Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions.
• Support AI/ML workflows with data preparation and analytical insights.
• Follow Agile methodologies and contribute to continuous improvement initiatives.

Experience Required:

• 5 - 8 years of experience in Data Analysis and AI/ML-related workflows.
• Strong hands-on experience in Python, Pandas, NumPy, SQL, and data analysis libraries.
• Experience with Hadoop and handling large-scale datasets.
• Knowledge of AI/ML concepts including supervised learning, unsupervised learning, and model metrics.
• Experience with data cleaning, transformation, and validation techniques.
• Exposure to Apache Spark, Jupyter Notebook, Git, Azure, AWS, and Agile methodologies is an added advantage.

Education: Any Graduation

Key Skills

Education

Any Graduate