• Led the development and optimization of data pipelines, ensuring efficient data collection, transformation, and integration from multiple sources, improving operational efficiency.• Conducted in-depth data analysis using Python, SQL, and R to identify key business trends and deliver actionable insights for data-driven decision-making.• Implemented machine learning models to forecast customer behaviors and trends, enhancing predictive analytics and supporting strategic planning.• Developed and maintained dashboards using Tableau and Power BI, visualizing complex datasets to provide stakeholders with real-time data insights and reporting.• Utilized big data technologies like Spark and Hadoop to manage and process massive datasets, enabling scalable and high-performance analytics.• Collaborated with cross-functional teams to design and implement ETL workflows, ensuring data consistency, accuracy, and quality across the entire pipeline.• Performed statistical analyses and A/B testing to evaluate the effectiveness of marketing campaigns, optimizing customer engagement and sales strategies.• Led data governance and data quality initiatives, establishing best practices to ensure the accuracy, integrity, and security of enterprise-wide data.• Developed custom scripts in Python and R for automating data extraction, cleaning, and analysis, significantly reducing manual efforts and increasing productivity.• Worked with cloud platforms such as Azure and AWS to build and deploy scalable data solutions, facilitating seamless data integration and analysis across cloud environments.• Provided mentorship and training to junior analysts, fostering a collaborative environment and ensuring best practices in data analysis and reporting.• Engaged in continuous learning of emerging data analysis tools and techniques, staying updated with industry trends and applying them to enhance data management processes.

• Gathered, cleaned, and transformed large datasets from multiple sources, ensuring high data quality and integrity for accurate insights.• Conducted advanced statistical analysis, utilizing tools like Python and SQL to extract meaningful trends that directly influenced strategic business decisions.• Developed, optimized, and maintained relational databases, improving data storage efficiency and retrieval processes by 20%.• Partnered with cross-functional teams to translate complex business requirements into technical data solutions, enhancing operational workflows.• Generated insightful reports and dashboards using Tableau and Power BI, providing real-time data visualizations for informed decision-making.• Utilized data mining techniques to identify key patterns and opportunities for growth, driving improvements in customer behavior analysis.• Implemented automation scripts in Python to streamline data extraction and cleaning processes, reducing manual effort by 30%.• Played a key role in optimizing ETL workflows, ensuring seamless data integration, consistency, and scalability for large-scale data projects.• Conducted exploratory data analysis (EDA) to uncover insights that led to innovative solutions, improving efficiency across various business departments.• Assisted in data migration from legacy systems to cloud platforms, leveraging Azure and AWS for improved scalability and performance.• Built predictive models using machine learning algorithms to forecast business outcomes, improving predictive analytics accuracy by 15%.• Ensured compliance with data governance standards, maintaining high standards of data quality, accuracy, and security across all datasets.