Job Summary: Data Science Analyst to analyze and process data, providing key insights to support decision-making in Credit Card Risk and Collections. Key Highlights: 1. Develop advanced analytical models and automation solutions. 2. Identify market needs and best practices for continuous improvement. 3. Collect, clean, and analyze data to generate insights. Fashion’s Park, a leading apparel retail company in Chile, is seeking a Data Science Analyst for the Financial Business Management team. The purpose of this position is to effectively analyze and process data to deliver key insights supporting decision-making, aligned with the strategies and requirements of Fashion’s Park’s Credit Card Risk and Collections area. Key responsibilities include: Collecting, cleaning, and analyzing data related to operations and area requirements. Executing development and generation of insights for decision-making. Identifying market needs, standards, and best practices, participating in the development and continuous improvement of the area. Enhancing operational efficiency and designing report generation processes. Developing advanced analytical models and automation solutions. Fashion’s Park is a family-oriented apparel retail chain employing approximately 3,000 people across Chile and China. With over 35 years of history and 100 stores spanning from Arica to Punta Arenas, we have established ourselves as an approachable and accessible brand. Our purpose is "To make those who choose us happy," delivering a unique and memorable shopping experience. To stay updated on our latest news, fashion trends, and promotions, follow us on social media: **Instagram:** @Fashions\_park **Facebook:** @tiendasfashionspark X: @Fashions\_Park\_ * ️ YouTube: @TiendasFashionsPark **LinkedIn:** Fashion’s Park Requirements Proficiency in SQL and Python. Power BI expertise. Degree in Industrial Engineering, Business Engineering, Computer Engineering, or Data Science. Benefits Staff cafeteria Supplementary health insurance National Holidays and Christmas bonuses Quarterly bonuses