- Designed and implemented interactive dashboards in Tableau and Power BI, resulting in a 35% increase in data-driven decision-making across departments.- Collaborated with stakeholders to define KPIs and created BI solutions using SQL and Tableau, improving reporting efficiency by 40%.- Leveraged advanced Excel features like pivot tables, VLOOKUP, and macros to streamline data analysis processes, reducing report generation time by 30%.- Optimized SQL queries and database indexing, reducing query processing time by 60% and improving report generation speed.- Automated data collection and cleansing using Python (Pandas, NumPy), improving data accuracy by 25% and reducing manual effort by 55%.- Built real-time data streaming applications with Kafka and Spark Streaming, ensuring low latency processing for critical operations.- Developed and automated ETL pipelines using Python, SQL, and Apache Airflow, reducing data processing time by 50% and improving data accuracy by 30%.- Conducted market trend analysis using R and SQL, providing insights that boosted sales by 15%.- Built and trained a machine learning model for customer churn prediction using Python (scikit-learn) and achieved 87% accuracy, leading to a 20% reduction in churn rates.

- Created dynamic dashboards in Power BI, utilizing DAX functions, reducing reporting time by 45% and enhancing real- time insights.- Developed a fraud detection system using machine learning algorithms (Logistic Regression, Random Forest) in Python, achieving a 92% success rate.- Conducted A/B testing and statistical analysis using R and Python, optimizing marketing campaigns and increasing conversion rates by 28%.- Developed complex financial models in Excel to forecast revenue and expenses, enabling a 15% increase in budget accuracy.- Built interactive reports in QlikView, utilizing Qlik scripting, empowering users with self-service analytics and reducing IT support requests by 30%.- Developed a recommendation engine using collaborative filtering in Python, increasing cross-sell and up-sell opportunities by 22%.- Automated data pipelines with Apache Airflow and SQL, ensuring 70% uptime and reliability for data workflows.- Led data integration projects with SSIS and SQL Server, improving data consistency across systems by 38%.- Created complex SQL queries for ad-hoc analysis, leading to a 20% improvement in operational efficiency.- Collaborated with developers to integrate data solutions using APIs and SQL, enhancing user experience and boosting application performance by 33%.

- Enhanced customer segmentation and targeting by analyzing CRM data, increasing marketing campaign effectiveness by 25% and customer retention by 18%.- Designed and maintained dynamic dashboards in Excel integrating data from various sources using Power Query, providing real-time insights that helped increase operational efficiency by 25%.- Led a team of 5 junior data analysts in developing data solutions, resulting in a 20% improvement in project delivery times and overall team productivity.- Migrated on-premise data systems to AWS cloud (Redshift, S3), achieving a 45% cost reduction and enhancing data accessibility.- Developed predictive models that forecast inventory needs with 90% accuracy, significantly reducing overstock and understock scenarios.- Utilized machine learning techniques in Python to segment customer data, enabling tailored marketing strategies that increased customer retention by 22%.- Created and maintained data documentation using Agile and JIRA, improving team knowledge sharing and onboarding efficiency by 25%.- Collaborated with IT and marketing departments to align data analytics with business strategies, enhancing the decision-making process and increasing operational transparency.- Implemented data backup and recovery solutions using SQL Server and AWS S3, ensuring data availability and security.