As a data scientist with around 6 years of experience in the semiconductor processes and manufacturing industry, I am dedicated to leveraging data to drive business success. I possess a strong background in statistical modeling, data analysis, and machine learning techniques, which has enabled me to deliver data-driven solutions to complex business problems. Throughout my career, I have worked closely with cross-functional teams to identify critical manufacturing challenges and deliver actionable insights to improve production efficiency, reduce costs, and increase product quality. I have a proven track record of leading data science projects from ideation to deployment and collaborating with both technical and non-technical stakeholders to ensure project success. My technical skills include statistical process control, design of experiments, and data mining techniques, which enable me to extract valuable insights from large datasets and build predictive models that optimize manufacturing processes. In addition to my technical skills, I am proficient in programming languages such as Python, R, and SQL, and have experience with data visualization tools such as Tableau and Power BI. I am passionate about leveraging my expertise in Industrial Analytics and automation to drive innovation and accelerate growth in the semiconductor and manufacturing industry.