•Led daily SCRUM meetings in an agile environment, retrospective meetings for issues, corporate suggestions, and decisions in code development.•Developed and maintained interactive Tableau dashboards to provide stakeholders with real-time insights into business performance, contributing to data-driven strategic decisions.•Automated the data extraction and reporting processes using Python and Power BI, which reduced manual reporting time by 30%, leading to more timely and accurate reporting across teams.•Created comprehensive Data Mapping Documents and collaborated with business teams to define transformation rules using SQL, ensuring a 20% improvement in data accuracy and consistency across systems.•Conducted advanced statistical analysis and predictive modeling using Python and R, uncovering key trends and insights that helped improve forecasting accuracy and strategic business decisions.•Performed requirement elimination, and analysis and conducted JAD sessions for communicating with stakeholders and project directors during iteration.•Worked closely with data engineers and business leaders to redesign the data pipeline architecture, improving data flow efficiency and reducing data processing time by 15%.•Optimized Python libraries such as Pandas, NumPy, and SciPy to automate data processing and perform advanced analysis, reducing data preparation time by 30% and providing actionable insights that informed key business strategies.

•Managed end-to-end ETL processes using SQL and Python, improving data integration efficiency and reducing processing time by 20%, which enhanced overall data quality for decision-making.•Conducted detailed data analysis using R and Excel, identifying key trends and providing actionable insights that guided business strategies and operational improvements.•Designed and deployed interactive Power BI dashboards that tracked key business metrics and key performance indicators, enhancing decision-making efficiency by 40% across business units.•Utilized machine learning models built with Scikit-Learn to predict customer behavior and optimize marketing strategies, directly contributing to the business’s growth and improving targeted campaigns.•Led data cleansing and transformation efforts, ensuring that the datasets used for analysis were high quality and accurate, significantly reducing data errors and improving the reliability of reports.•Partnered with business stakeholders to gather detailed requirements for data solutions, ensuring that the solutions provided were aligned with business needs and drove actionable insights for better decision-making.•Led cross-departmental workshops to train team members on data analysis best practices and data visualization tools, improving team proficiency and collaboration, which resulted in a 25% increase in departmental productivity.