Arushi Bansal

• Design and refine statistical and machine learning models (Python, SQL, SAS) to detect patterns in large-scale transactional data, improving predictive accuracy and business decision-making. •Develop and maintain experimentation frameworks incorporating hypothesis testing, sampling design, and lift analysis, alongside analytics dashboards (Tableau, Power BI) to measure strategy performance and enable real-time monitoring. •Modernize and optimize enterprise ETL pipelines by migrating 40+ reporting processes to Snowflake/SQL, improving query performance, scalability, and cross-functional data accessibility. •Conduct advanced data analyses using anomaly detection, root-cause analytics, and segmentation techniques to uncover trends and drive operational improvements.

• Delivered advanced analytics solutions including forecasting models, predictive modeling, and causal inference approaches (Python, SQL, Databricks) to provide clients with scenario analysis and data-driven strategy recommendations. • Designed and deployed interactive dashboards (Power BI, Tableau) with automated data quality checks, applying data modeling best practices (star schema, snowflake schema) to improve performance tracking and decision-making. • Spearheaded GenAI proof-of-concepts (POCs) showcasing applications in summarization, content generation, and data exploration, enabling clients to explore emerging AI capabilities.

• Led a team to build regression and ML models (Random Forest, XGBoost) predicting labor hours with 76% accuracy, and delivered Power BI dashboards to optimize workforce allocation.

• Implemented customer segmentation techniques (K-means clustering, regression analysis) with feature engineering to identify traveler groups and drive targeted ancillary sales strategies. • Executed A/B testing and hypothesis-driven experiments to evaluate booking features, measure lift, and improve conversion rates. • Optimized inventory and pricing decisions across international routes using forecasting and time-series techniques, driving improvements in revenue efficiency. • Designed interactive dashboards and automated ETL reporting pipelines (SQL, Python, Tableau) to streamline KPI monitoring, data governance, and reporting automation, saving hours of manual effort weekly. • Collaborated with commercial, product, and operations teams to define KPIs, translate analytical insights into strategy, and deliver executive-ready performance reporting

• Conducted market research and pricing sensitivity analysis to evaluate consumer concepts and generate insights for client strategy. • Supported survey design, data analysis, and client presentations, contributing to research reports and executive-ready decks.

• Analyzed transaction patterns and anomalies, developing dashboards to track digital wallet usage and performance.