Summary: Performed data mining and predictive modeling using Python, resulting in the identification of key drivers impacting sales performance.Utilized basic SQL queries and joins to extract and combine data from multiple relational databases, ensuring data integrity for reporting purposes.Collaborated with marketing team to develop customer segmentation strategies based on demographic and behavioral attributes, resulting in a 25% increase in targeted marketing campaign ROI.Conducted cohort analysis to assess the lifetime value of customers, leading to the optimization of acquisition and retention strategies.Utilizd data visualization tools like Power BI and Tableau to create insightful reports and dashboards for business stakeholders.Conducted data profiling and cleansing activities to improve data accuracy and integrity, resulting in more reliable analyses.Collaborated with data engineering team to design and optimize ETL processes for efficient data extraction and transformation.Developed predictive models using machine learning algorithms to forecast customer behavior, resulting in a 20% improvement in marketing campaign targeting.Led cross-functional teams in the implementation of data governance and data privacy policies, ensuring compliance with relevant regulations.Technial Skills: Proficiency in languages, tools, and platforms used in data analysis like Python, SQL, Excel, Power BI etc.Statistical Knowledge: Understanding of statistical theories and methodologies relevant to data analysis.Data Cleaning and Preprocessing: Experience in preparing raw data for analysis, including cleaning, transformation, and integration.Data Visualization Skills: Ability to present complex results in an understandable and visually appealing format.Analtical Mindset: Evidence of problem-solving, critical-thinking abilities, and attention to detail.Technical skills:SQL (Structured Query Language)PythonPower BIDatabase ManagementData ModelingMachine LearningPredictive ModelingExcelData VisualizationData Cleaning