▪ Utilized SQL and Python for in-depth data analysis, providing critical insights that supported key strategic decisions and influenced organizational strategy.▪ Developed a key Data Science project at Uber, utilizing regression analysis, machine learning, and optimization algorithms to support data-driven decision-making, thereby improving operational efficiency and enhancing driver and customer satisfaction.▪ Participated in projects aimed at optimizing Uber's operational workflows, contributing to improvements in operational efficiency and the customer experience.▪ Engaged in the detailed operational framework of Uber, playing a key role in addressing strategic challenges through data analytics and practical problem-solving.▪ Contributed to the enhancement of product features and operational strategies, focusing on operational improvements and driver welfare, leading to tangible enhancements in operational performance.

Internship at Amazon Business▪ Spearheaded a Digital Transformation Project: Led the digitization of a key DG performance report by creating an automated online dashboard, significantly improving data accessibility and analysis, and aiding in more informed operational decision-making.▪ Leveraged Data-Driven Insights for Client Solutions: Utilized advanced data analysis techniques to generate insights that informed client solutions, enabling a more targeted and effective approach in addressing client needs and preferences. This strategic use of data not only enhanced client satisfaction but also contributed to more refined business development strategies.▪ Collaborated Closely with Potential Clients: Worked directly with clients to understand their needs, using these insights to improve Amazon Business's customer acquisition strategies through enhanced value proposition development.▪ Facilitated Cross-Team Communication: Ensured effective collaboration between Munich and USA teams on a critical marketing project, integrating diverse feedback and guiding successful project delivery aligned with strategic objectives.

Data Science Project for Business Development▪ Successfully reduced operational costs by 30% within 3 months through innovative data analysis and process optimization.▪ Drove a 40% increase in benefits over 4 months by implementing advanced predictive analytics and data-driven decision-making strategies.▪ Enhanced customer satisfaction ratings by 20%, achieved by leveraging data insights to improve service delivery and customer engagement.▪ Collaborated across departments to integrate data insights, enhancing overall business efficiency and profitability.

Conducted a market research study as part of the "Management Survey Techniques" course in Master S2IE.▪ Conducted internal and external analysis of the company through benchmarking.▪ Used qualitative and quantitative analysis with SPSS software.▪ Developed strategic recommendations for the studied company.▪ Developed skills in market research and data analysis.

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