Description

Key Responsibilities:

• Collect, clean, preprocess, and analyze structured and unstructured data from multiple sources.
• Develop, train, evaluate, and deploy Machine Learning models for classification, regression, clustering, forecasting, and recommendation systems.
• Perform exploratory data analysis (EDA), statistical modeling, hypothesis testing, and feature engineering.
• Build predictive analytics solutions using supervised and unsupervised machine learning techniques.
• Develop data visualization dashboards and reports using Power BI, Tableau, or Python visualization libraries.
• Collaborate with business stakeholders, Data Engineers, Product Managers, and Software Engineers to translate business problems into analytical solutions.
• Optimize machine learning models for scalability, accuracy, and production deployment.
• Work with large-scale datasets using distributed computing frameworks such as Spark and Databricks.
• Deploy machine learning models using MLOps best practices and cloud platforms such as AWS, Azure, or GCP.
• Monitor model performance, retrain models, and continuously improve predictive accuracy.
• Document analytical methodologies, model performance, and technical solutions while supporting production environments

Key Skills

Education

Any Gradute