Core Competencies • Data Cleaning & Preprocessing: Ensuring data accuracy, consistency, and readiness for analysis. • Statistical Analysis: Using advanced statistical methods to analyze data, identify patterns, and extract meaningful insights. • Data Visualization: Creating impactful and easily interpretable data visualizations using tools like Tableau, Power BI, and Excel. • Reporting & Dashboards: Designing and automating custom reports and dashboards to enable efficient business tracking. • Business Intelligence: Translating data insights into strategic recommendations that drive growth and performance improvements. Tools & Technologies • Data Visualization Tools: Tableau, Power BI, Excel • Data Processing & Analysis: Google Sheets, Python (Pandas, Numpy), R • CRM & Business Tools: Shopify, HubSpot, Shipstation, Funnelkonnek, Stripe, Invoice • Project Management & Collaboration: Trello, Asana, Slack, Microsoft Teams Featured Projects 1. Sales Performance Analysis for E-Commerce Company • Objective: Analyze sales data from an e-commerce platform to identify key factors influencing revenue growth and customer retention. • Tools Used: Shopify, HubSpot, Shipstation, Stripe, Funnelkonnek, Invoice, Google Sheets • Key Actions: o Cleaned and preprocessed large datasets with transaction records, customer information, and product details. o Conducted exploratory data analysis (EDA) to uncover trends and patterns in sales performance over time. o Created interactive dashboards and reports in Excel to visualize key metrics, including monthly sales growth, top-performing products, and customer segments. • Outcome: o Delivered actionable insights that resulted in a 15% improvement in customer retention in the following quarter. o Provided data-driven recommendations that helped optimize marketing strategies and product offerings. 2. Marketing Campaign Analysis for Retail Brand • Objective: Assess the effectiveness of a recent marketing campaign and its impact on sales. • Tools Used: Power BI, Excel, Google Analytics, CRM tools • Key Actions: o Analyzed sales data from before, during, and after the campaign to measure performance. o Utilized A/B testing results to identify which aspects of the campaign drove the most conversions. o Developed a comprehensive Power BI dashboard to present key findings to the marketing and sales teams. • Outcome: o Identified that targeted promotions increased sales by 18%. o Provided recommendations for future campaigns based on analysis of customer segments and product preferences. 3. Customer Segmentation & Retention Analysis • Objective: Segment customers based on purchasing behavior to improve retention strategies. • Tools Used: Google Sheets, Tableau, CRM tools • Key Actions: o Conducted cluster analysis using historical purchase data to identify key customer segments. o Analyzed retention metrics and behavior patterns for each segment. o Created dynamic Tableau dashboards to present customer insights and retention trends. • Outcome: o Developed targeted retention strategies for each customer segment, improving engagement and reducing churn by 10%. 4. Financial Reporting & Forecasting for Wholesale Business • Objective: Automate financial reporting and implement predictive forecasting models for revenue and expenses. • Tools Used: Excel, Power BI, Google Sheets, Salesforce • Key Actions: o Designed automated reporting systems for monthly financial reviews using Excel and Power BI. o Integrated sales and expense data into a predictive forecasting model to project future financial outcomes. o Provided insights into trends, seasonality, and potential risk areas in financial performance. • Outcome: o Improved financial reporting accuracy and speed, reducing manual reporting time by 40%. o Helped leadership make more informed financial decisions with clearer projections.