Worked with large-scale, structured, and unstructured datasets to create predictive, forecasting, optimizing Machine learning models. Worked on SQL, Python and R languages to the design, development, and maintenance of ongoing ML Models, analyses, dashboards, etc. to drive key business decisions.  Having good exposure on marketing analytics, Customer Feedback analysis, Building recommendation models and Forecasting. Experience with building and/or fine-tuning large language models, as well as traditional machine learning models. Worked in building ETL pipeline for data ingestion, data transformation, data validation on cloud service GCP, working along with data steward under data compliance. Developed ETL pipelines to extract data from an external API’s and loading them into data warehouse. Created impactful dashboards in power BI for data reporting. Extracted, Interpreted, and analyzed data to identify key metrics and transform data into meaningful, actionable information. Proficiency in Predictive and data Modeling, Data mining Methods, Factor Analysis, ANOVA, Hypothetical testing, normal distribution and other advanced statistically Developed predictive models using Decision Trees, Random Forest, Naïve Bayes, Logistic Regression, Cluster Analysis, and Neural Networks Worked on Data Build Tool for transformations in ETL process, AWS lambda, AWS SQS. Migrated an existing on-premises application to AWS. Used AWS services like EC2 and S3 for small data sets processing and storage, Experienced in Maintaining the Hadoop cluster on AWS EMR. Model Management - Built a centralized hub to host and manage all the Machine learning, Deep learning and Nlp Models with the help of CI/Cd pipelines, Micro services, Python, flask, Seldon core