• Optimization of lifecycle campaigns in customer journey focused on the retention leading to improvements in churn rate and incremental commercial performance.• Continuous tracking and end to end maintenance of campaign selection pipelines (CI/CD) from the engineering perspective (SQL, Python, Databricks).• Designing, launching and post analysis of multiple A/B tests via statistical testing, cohort analysis, unit economics • Worked closely with the product development team to analyze customer feedback and market trends, contributing to the successful launch of new products.

• Analyzed patient data to support clinical research and improve patient outcomes, contributing to a 10% improvement in treatment effectiveness.• Assisted in the development of predictive models to forecast patient admission rates, aiding in resource allocation and staff scheduling.• Created detailed reports and visualizations for senior management to monitor key performance indicators and make data-driven decisions.• Collaborated with IT teams to ensure data integrity and security during system upgrades and migrations.

• Lead a team of data analysts in developing predictive models to identify customer churn and optimize retention strategies, resulting in a 15% reduction in churn rates.• Designed and implemented an automated reporting system using Python and SQL, reducing manual reporting time by 40%.• Collaborated with marketing and finance teams to analyze campaign performance, driving a 10% increase in ROI.• Spearheaded the migration of data analysis workflows to cloud-based platforms, enhancing data accessibility and processing speed.• Presented findings and actionable recommendations to senior management, resulting in a 15% reduction in churn over six months.• Worked closely with the marketing team to develop tailored campaigns for each customer segment, resulting in a 20% increase in campaign engagement and a 15% boost in sales.