As a data analyst, I have a talent for data-storytelling, presentation, and transforming complex data into actionable insights that drive decision-making. With a background in software testing, transitioning into data analytics allowed me to apply my expertise in performance testing, data analysis, and automation. My motivation stems from a passion for data-driven decision-making, where I can leverage technical skills in Python, SQL,Excel, and Power BI to deliver impactful solutions. This transition has enhanced my ability to bridge gaps between data, technology, and business strategy.I am a collaborative and approachable team member who values effective communication and timely delivery of tasks. I make it a priority to keep my peers informed of my progress and I am always ready to assist teammates when needed. I contribute to projects proactively, focusing on meaningful contributions rather than seeking recognition. My annual reviews reflect my commitment to being helpful and conscientious, with colleagues often highlighting my supportive nature and dedication to the team.My Background: 7+ years of experience working with financial, social media, and service logs data to extract insights and present them through concise reports and demos. My greatest strength is attention to detail and focus on data to answer business questions. 4 years of experience in a QA position to define and automate test cases that verify product requirements. Contribute to decisions in the architecture and design of test frameworks. Participate in test execution, issue identification, and resolution in support of the release. Conduct code reviews, and improve and maintain the quality of the automation code. Participated in A/B test execution, issue identification, and troubleshooting in support of the release testing, resulting in a 30% reduction in post-release issues and 70% test coverage. 3 years of experience as a Data Scientist. Developed statistical models for Cash Flow Prediction in Python using machine learning techniques. Improved the accuracy of the predictive models by 10% by optimizing the set of hyper-parameters in Neural Networks. Implemented data-driven models for Twitter Sentiment Analysis in Python by using real-time data collected with Twitter API. Used NLP techniques to extract insights from social media data and help companies realize customers' thoughts and opinions about their products.