Conducted market research and analyzed customer behavior data. - Prepared reports and presentations for clients showcasing data-driven insights. - Collaborated with cross-functional teams to address business challenges using data. - Assisted in creating and maintaining databases to support data analysis activities.Developed and maintained data pipelines for automated data extraction. - Performed statistical analysis and hypothesis testing on large datasets. - Identified data quality issues and implemented data validation procedures. - Contributed to the development of machine learning models for predictive analytics.

Assisted in data cleaning and preparation for analysis. - Conducted exploratory data analysis to identify trends and patterns. - Created visualizations and dashboards to present data insights to stakeholders. - Collaborated with team members to optimize data collection processes.• Source, interrogate and analyses data using various skillsets (e.g. data aggregation, data visualization, root cause & outlier analysis using statistics) to drive new insights supporting BAU & ad-hoc oversight activities.• Bring an understanding of technologies used in HLS domain (and other sectors) and role-model intellectual curiosity and continuous learning related to emerging technology. • Communicate effectively, collaboratively and challenge constructively to create rapport and establish trust.• Actively participate in business and/or analytics team activities and suggest ways of achieving objectives (standup, planning meeting, retrospectives)• Network and proactively connect with craft peers beyond the team scope.• Use previous knowledge and experience on data analysis and visualization to answer business questions in the most efficient way. Actively participate in business and/or analytics team activities and suggest ways of achieving objectives (standup, planning meeting, retrospectives)

• Part of data driven role utilizing advanced analytics in product development.• Conduct statistical analysis, hypothesis testing, and predictive modeling to support business initiatives in drug development process.Provide actionable recommendations based on data analysis to optimize operational efficiency and improve decision-making in drug development process.