Implemented software development life cycle (SDLC) methodologies (Agile, Waterfall) to enhance team productivity by15%,achieved profound knowledge of data modeling, assessing data sources, and data warehousing. Conducted statistical analysis and modeling in R and Python, resulting in a 10% decrease in customer churn rate. Optimized data processing using Python integrated development environments (IDEs) such as PyCharm and Visual StudioCode,along with data manipulation libraries like matplotlib, NumPy, and Pandas, reducing data cleaning time by 20%. Produced impactful data visualizations, reports, and schedules using Tableau, boosting data visualization efficiency by25%. Transferred data to AWS S3 and used Redshift for data manipulation, yielding a 30% improvement in data processingspeed. Led extract, transform, and load (ETL) procedures with Informatica and SQL Server Integration Services (SSIS),integrating diverse datasources into a centralized data warehouse and enhancing data availability by 40%. Applied data analysis skills, including extracting and mapping data from MySQL, t o enhance data accuracy andconsistency by15%. Developed machine learning models such as Linear Regression, Logistic Regression, Random Forest, and K-NearestNeighbors(KNN), achieving a 20% boost in predictive accuracy and optimizing decision -making processes. Developed and maintained automated data pipelines using Python and AWS services, reducing manual data handling by 35% andensuring consistent, error-free data flow

 Deployed Agile methodology and actively participated in daily stand -up, showcase, and sprint retrospective meetings,resulting in100% on-time project delivery. Constructed SQL and Python scripts for data reconciliation, achieving a 20% enhancement in data accuracy and reducingreconciliation time by 15%. Conducted Exploratory Data Analysis using pandas, NumPy, seaborn, SciPy, Matplotlib, and Scikit-learn packages inPython,uncovering valuable insights and patterns that led to a 25% boost in revenue. Executed ETL processes using Informatica mappings, ensuring seamless data integration within the Data Warehouse andreducingdata integration errors by 30%. Created multiple data visualization solutions during the Power BI business preview phase, enhancing data representationandenabling stakeholders to make informed decisions, and 40% increase in data visualization. Successfully worked with various AWS services such as EC2, EBS, ASG, RDS, and R53, optimizing resource utilizationandreducing infrastructure costs by 20%. Managed SQL Server databases, maintaining data security and compliance with a 100% data confidentiality rate. Used advanced Excel functions to generate spreadsheets and pivot tables for report generation, reducing report generationtime by25% and improving 15% data accuracy. Designed, built, and delivered data integration, extraction, and migration projects using Data Stage to GCP, achieving 100%successful implementation and reduced 30% data transfer time. Accessed external files and generated permanent SAS data sets, improving data accessibility and reduced 20% data retrieval time.Collaborated with internal technical teams, performed data analysis, and conducted assessments for successfulimplementation of data corrections in the data warehouse, achieving a 98% accuracy rate in data correction andimproving overall system performanceby 15%

Established analytics goals and used advanced Google Analytics features to extract customer insights, resulting in acomprehensive understanding of customer behavior and a 25% increase in conversion rate. Prepared analytic reports on user demographics and behavior using Microsoft Excel, Word, and PowerPoint, providingactionableinsights for decision-making and contributing to a 15% improvement in marketing campaign targeting. Presented findings to senior leadership, informing critical decisions and increasing brand recognition and customer base by20%. Used customer data analysis to make targeted product recommendations, resulting in a 30% increase in add-on salesand improved cross-selling opportunities. Carried out data-driven strategies to optimize customer engagement and retention, leading to a 10% increase in customersatisfaction and a 15% improvement in customer retention rate. Cooperated cross-functionally to implement customer-centric initiatives, reducing complaints by 20% and enhancing brandreputation.