• Adopted Agile methodologies to oversee iterative and adaptive data analysis projects, achieving a 30% improvement in project and efficiency, ensuring responsiveness to evolving business needs. • Implemented machine learning models and analytics solutions using Python, R, and SQL to address business challenges and streamline operations. • Established visually compelling reports and dashboards with Tableau, enhancing data-driven decision-making by clearly presenting key metrics and trends, increasing stakeholder engagement by 50%. • Conducted comprehensive analysis and processing of extensive datasets using Apache Spark and PySpark, significantly boosting the efficiency and velocity of data operations. • Orchestrated the deployment and administration of big data solutions on Azure and Databricks, facilitating scalable and high-performance data analytics capabilities. • Handled and analyzed unstructured data using MongoDB, implementing NoSQL querying and aggregation for flexible data management and analysis.

Implemented Waterfall methodologies for structured project execution, ensuring clear milestones and deliverables, achieving a 95% adherence to project timelines. • Leveraged R, SAS, and Jupyter Notebook for statistical analysis and modeling, improving prediction accuracy by 20%. • Conceptualized Seaborn, SciPy, Scikit Learn, and ggplot2 for advanced data visualization and analysis, leading to actionable insights that optimized business strategies. • Created interactive dashboards and reports in Power BI, facilitating data-driven decision-making and enhancing stakeholder understanding by 30%. • Implemented AWS cloud technologies to develop scalable data solutions, enabling seamless data storage, processing, and analytics. • Employed DataBricks for scalable data processing workflows and collaborative analytics, boosting operational efficiency by 30% and enabling seamless large dataset integration. • Expertly managed MySQL databases to extract, transform, and analyze structured data, ensuring precision in reporting and strategic decision-making Implemented Waterfall methodologies for structured project execution, ensuring clear milestones and deliverables, achieving a 95% adherence to project timelines. • Leveraged R, SAS, and Jupyter Notebook for statistical analysis and modeling, improving prediction accuracy by 20%. • Conceptualized Seaborn, SciPy, Scikit Learn, and ggplot2 for advanced data visualization and analysis, leading to actionable insights that optimized business strategies. • Created interactive dashboards and reports in Power BI, facilitating data-driven decision-making and enhancing stakeholder understanding by 30%. • Implemented AWS cloud technologies to develop scalable data solutions, enabling seamless data storage, processing, and analytics. • Employed DataBricks for scalable data processing workflows and collaborative analytics, boosting operational efficiency by 30% and enabling seamless large dataset integration.