• Utilized SQL and Python for data extraction, cleaning, and analysis; conducted exploratory data analysis (EDA) to identify key metrics and trends that guided business strategy.• Created predictive models using machine learning algorithms to forecast sales and customer trends, achieving a 15% increase in forecast accuracy.• Conducted complex statistical analyses, including regression and clustering, to uncover insights and trends that informed strategic business decisions and increased operational efficiency by 25%.• Collaborated with 10+ cross-functional teams to analyze business objectives and deliver tailored data-driven solutions, improving operational efficiency by 20%.• Developed custom scripts and utilized Python, SQL, and R tools to automate data collection, cleansing, and transformation tasks.• Conducted a comprehensive data analytics of client behavior by leveraging Python libraries to develop insightful reports using sales data from 30+ geographies.• Utilized big data technologies such as Hadoop and Spark to process and analyze large datasets, providing insights that informed strategic business decisions.• Utilized AWS data-related services such as Glue, Athena, Kinesis, and Data Pipeline for efficient data management and analysis.• Designed and implemented impactful Power BI reports, increasing data understanding by 25% and effectively presenting key insights to stakeholders.• Skilled in extracting, cleaning, and transforming large datasets from various sources using SQL, Excel, and Python to ensure data accuracy and integrity.• Developed predictive models using machine learning algorithms to forecast customer behavior, achieving a 20% increase in forecasting accuracy and supporting targeted marketing campaigns.• Designed and implemented visualizations and dashboards that highlighted key performance indicators (KPIs), aiding in data-driven decision-making

• Utilized tools such as SQL, Python, and R for data extraction, cleaning, and analysis; created dynamic dashboards and visualizations using Power BI and Tableau to support data-driven decision-making.• Designed and maintained complex databases in SQL Server and MySQL; optimized queries for performance improvements, reducing data retrieval times by up to 40%.• Streamlined data processing workflows by implementing automation scripts in Python, reducing manual effort by 30% and increasing overall efficiency.• Pioneered the implementation of custom data integrations which involved creating complex stored procedures and utilizing Common Table Expressions (CTEs) for optimized data loading processes, significantly improving the customer onboarding experience by streamlining technical issues resolution• Established and maintained proactive communication channels with key customers, understanding their business needs and recommending tailored data management and analysis solutions using modern data warehousing tool (Snowflake) and BI tool (Tableau), this initiative helped in nurture customer relationships and boosting their business growth.• Created and optimized relational and NoSQL databases using MySQL, PostgreSQL, and MongoDB, resulting in enhanced data retrieval and processing speeds.• Spearheaded the development of a new feature for a major enterprise application, increasing user engagement by 30% and receiving positive feedback from clients. • Played a key role in the development and maintenance of data pipelines using Python, ensuring seamless ELT processes and the integrity of data analysis projects.• Implemented performance tuning techniques that decreased application load times by 50%, significantly enhancing the user experience.• Conducted in-depth analyses of customer behavior and market trends, resulting in a 15% increase in customer retention through targeted marketing strategies.