• Conducted comprehensive data analysis on soil conditions to develop innovative agricultural technologies for unfertile hilly regions.• Collaborated with interdisciplinary teams to secure patents for data-driven agricultural solutions.• Utilized machine learning algorithms to predict optimal crop growth conditions and enhance vegetable yield.• Applied Geographic Information Systems (GIS) for precise soil mapping and targeted irrigation strategies.• Developed and tested data models to improve soil fertility and irrigation efficiency, supported by USERC grants.• Generated detailed reports and visualizations to communicate findings and recommendations to stakeholders.

• Built a machine learning model for real-time fraud detection using Python and TensorFlow.• Automated data pipelines with Apache Airflow and integrated CI/CD practices, enhancing data processing speed by 10% and ensuring seamless workflow management.• Designed interactive dashboards in Power BI and Tableau for faster decision-making.

• Leveraged SQL, Google BigQuery, and proprietary systems to enhance business retention and conversion rates using predictive analytics.• Identified and resolved 14-25 data quality issues with Kusto (Azure Data Explorer), improving reporting accuracy and data integrity.• Streamlined the creation of weekly and daily analytical reports using SQL, Python, and advanced BI tools like Power BI and Tableau.• Implemented machine learning algorithms to predict customer behavior, boosting retention by 15%.• Utilized cloud platforms such as AWS and Azure for scalable data storage and processing solutions.• Developed ETL pipelines using Apache Spark for efficient data transformation and loading.• Applied advanced data visualization techniques in Power BI to create insightful dashboards for executive reporting.• Conducted A/B testing and statistical analysis to optimize marketing strategies and improve conversion rates.