Stevenson Jacob

Highly motivated graduate seeking an entry-level position as a Data Analyst. Proficient in data analysis and database management, with a strong desire to contribute to innovative projects in a dynamic professional environment.

Experienced Senior Associate skilled in SQL, Python, advanced MS Excel, Power BI, and Statistics Data Analysis. Works closely with cross-functional teams to interpret data sets and derive meaningful insights. Demonstrates effective communication, collaborative teamwork, adept problem-solving, and strong time management. Committed to continuous skill enhancement and learning. Driven to optimize processes and streamline operations for team efficiency.

Date of Birth: 07/11/99

• Kannada
• English
• Hindi
• Tamil
• Malayalam

• Microsoft Power BI Data Analyst Professional Certificate
• Crash Course on Python
• SQL - MySQL for Data Analytics and Business Intelligence
• Microsoft Excel - Excel from Beginner to Advanced

• Project Title: Data Analyst - E-Commerce Recommendation Engine
• Description: Dynamic and results-driven Data Analyst with expertise in developing and optimizing recommendation engines for e-commerce platforms. Proficient in leveraging SQL for data analysis, user segmentation, and recommendation generation to enhance user experience and drive sales.
• Key Result Areas:
• Developed a robust recommendation engine for an e-commerce platform using SQL.
• Analyzed user interactions, product data, and past purchases to identify trends and patterns.
• Segmented users based on their behavior and preferences to deliver personalized product recommendations.
• Evaluated and optimized the recommendation engine's performance to enhance user engagement and increase conversion rates.
• Highlights
• Created a relational database schema for storing user interactions, product details, and past purchases. Employed SQL for exploratory data analysis to uncover insights into user behavior and product preferences.
• Applied user segmentation techniques to identify distinct personas and tailor recommendations.
• Developed recommendation algorithms using SQL joins, subqueries, and aggregation functions for personalized product suggestions.
• Assessed recommendation engine performance with metrics like click-through rates, conversion rates, and user engagement.
• Integrated and deployed the recommendation engine into the e-commerce platform's backend, ensuring real-time recommendations and seamless data synchronization.