I am passionate about working with data and helping a company put the data it already collected to use, in order to increase the company’s efficiency and maximize profits. Keen on conceptual understanding, integration of Computer Vision & Machine Learning. Have an eclectic taste in Data Analytics and Data Visualization. #obsessedwithdata Currently 🗓: Working as a Senior Data Analyst at Chewy, I played a pivotal role in driving data-driven decision-making across the organization. My responsibilities extended beyond traditional reporting, encompassing data optimization, automation, and strategic analytics. One of my significant accomplishments was optimizing 2G sites reporting and creating weekly operational business reports using SQL (Vertica) and Tableau. These reports provided critical insights to senior operations leadership and the C-Suite, empowering them to make informed decisions that enhanced operational efficiency. I also streamlined data management by centralizing and redefining data sources, consolidating more than 100 metrics into a single GitHub SQL script. This effort not only improved data accuracy but also significantly increased efficiency in data retrieval and analysis. Work Experience 👨‍💻 I have 2+ years of work experience working with American Express and KPMG, I possess an innate ability to connect the dots and a never give up attitude towards the work I get. I am quick and enthusiastic learner, good with analytical and problem-solving skills. Leader and a team player. Proactive individual bearing the ability to easily connect with people and gain trust. Dreams & Aspirations 🏆: I’d love to work as a Data Scientist to help the clients and firms in analysing the patterns and insights from the raw data using my technical skills. Technical Skills Tools/App Suites : SSIS, SQL Developer, Microsoft Excel, Oracle, Informatica PowerCenter, JIRA, Control-M Visualization: MS Power BI, Tableau, MS Excel Languages: R, Python (Scikit-learn, Pandas, NumPy, Seaborn, Matplotlib), XML, SQL, HTML Databases: Oracle, Microsoft SQL Server, Microsoft Access, MySQL, Hive, MongoDB, PostgreSQL