Esma Gunes

Lead Data Scientist

Cadillac•  April 2022 - August 2024

Led a team of data scientists in the development, optimization, and deployment of machine learning models, including a daily sales prediction model that improved accuracy by 12%, driving business decision-making. Collaborated with cross-functional teams across sales, marketing, and finance to ideate and implement machine learning solutions, optimizing sales strategies and increasing monthly sales by $8 million. Designed scalable, automated processes for large-scale data analysis and model implementation, streamlining workflows and reducing incentive spending by 18%. Directed the development of data pipelines using AWS, Hadoop, and Hive for enterprise-level applications, ensuring data transformation and validation across large datasets. Created "Offer Intelligence" dashboards using SQL and Python, automating previously manual workflows and delivering actionable insights to executive leadership. Led monthly presentations to executive-level stakeholders, providing data-driven insights that informed strategic decisions across departments.

Senior Data Scientist/Developer

Zions Bank•  May 2020 - April 2022

Led the analysis of large datasets to identify trends and opportunities for customer acquisition and retention, driving a 10% increase in customer satisfaction. Defined and designed the ETL processes to support data migration and integration, ensuring data accuracy and compliance with industry regulations. Managed and optimized dashboards and visualizations in Tableau, enabling real-time access to key performance metrics for executive stakeholders and improving decision-making efficiency. Evaluated A/B testing results to study the effectiveness of marketing campaigns, optimizing customer outreach and increasing ROI by 12%.

Production Support/Data Scientist

Zions Bank•  April 2017 - May 2020

Provided critical production support for data systems, minimizing downtime and ensuring data availability for key business operations. Enhanced data visualization tools and reports, driving data-driven decision-making across multiple departments. Collaborated with technical teams to identify and resolve data quality issues, improving the reliability and integrity of business intelligence systems.