I’m Ananya, a computing and AI student with hands-on experience applying data analytics, machine learning, and automation to real-world problems in the pharma and medtech industry. I’ve worked in Switzerland with global organizations including Johnson & Johnson and Kenvue, where I supported data-driven decision-making across complex, regulated environments. My work has ranged from building data pipelines and analytical frameworks to designing automation and reporting solutions that support senior stakeholders. At Johnson & Johnson, I contributed to enterprise automation initiatives using tools such as Power Automate, Power BI, Salesforce, and ERP systems, helping teams identify efficiency gains and develop business cases for large-scale process improvements. At Kenvue, I worked on data lineage, graph-based data modeling, and statistical analysis, handling large, messy datasets and translating them into actionable insights for engineering and manufacturing teams. What sets me apart is my ability to bridge technical depth with business context. I’m comfortable working with raw, imperfect data, selecting appropriate statistical or machine learning approaches, and communicating results clearly to both technical and non-technical audiences. With a strong foundation in Python, statistics, machine learning, and data engineering, combined with experience in cross-functional, stakeholder-facing roles, I focus on delivering solutions that are not just technically sound, but genuinely useful. I’m motivated by projects at the intersection of data, technology, and impact, particularly in life sciences and healthcare, where high-quality analysis and reliable systems directly support better outcomes.…I’m Ananya, a computing and AI student with hands-on experience applying data analytics, machine learning, and automation to real-world problems in the pharma and medtech industry. I’ve worked in Switzerland with global organizations including Johnson & Johnson and Kenvue, where I supported data-driven decision-making across complex, regulated environments. My work has ranged from building data pipelines and analytical frameworks to designing automation and reporting solutions that support senior stakeholders. At Johnson & Johnson, I contributed to enterprise automation initiatives using tools such as Power Automate, Power BI, Salesforce, and ERP systems, helping teams identify efficiency gains and develop business cases for large-scale process improvements. At Kenvue, I worked on data lineage, graph-based data modeling, and statistical analysis, handling large, messy datasets and translating them into actionable insights for engineering and manufacturing teams. What sets me apart is my ability to bridge technical depth with business context. I’m comfortable working with raw, imperfect data, selecting appropriate statistical or machine learning approaches, and communicating results clearly to both technical and non-technical audiences. With a strong foundation in Python, statistics, machine learning, and data engineering, combined with experience in cross-functional, stakeholder-facing roles, I focus on delivering solutions that are not just technically sound, but genuinely useful. I’m motivated by projects at the intersection of data, technology, and impact, particularly in life sciences and healthcare, where high-quality analysis and reliable systems directly support better outcomes.WWWW…