Data Scientist – Fashion DTC Brand Open for LATAM 📍 Location: Remote 📄 Type: Full-time Key Responsibilities Own the Data Pipeline – Lead the collection and integration of data from databases, APIs, and third-party tools, ensuring high-quality, reliable data. Uncover Hidden Insights – Conduct deep exploratory analysis to identify predictive patterns and strategic business opportunities. Develop Intelligent Solutions – Build and deploy advanced predictive models and machine learning algorithms to optimize decision-making and operational processes. Bring Data to Life – Create dynamic dashboards and visualizations that communicate complex findings in a clear, actionable way for senior stakeholders. Lead Data-Driven Strategy – Manage analytical projects from concept to execution, providing insights that directly influence business growth. Collaborate Across Teams – Work closely with technical and non-technical teams to implement data-driven solutions and ensure alignment on key strategies. Stay Ahead of Trends – Continuously research and integrate new methodologies and technologies to enhance analytical capabilities. Requirements What We’re Looking For 5+ years of experience in data science, analytics, or a related field. Expertise in SQL and Python, with a track record of developing robust data solutions and models. Strong proficiency in data visualization tools such as Looker, Tableau, or similar platforms. Deep understanding of statistical methods, predictive modeling, and machine learning applications. Ability to independently drive complex analytical projects from concept to implementation. Strong problem-solving skills with the ability to translate data-driven insights into strategic business recommendations. Excellent communication and presentation skills to effectively engage both technical and non-technical audiences. Passion for the fashion or e-commerce industry is a strong plus. This role is ideal for someone who can turn data into actionable intelligence that drives real business impact. If that sounds like you, we’d love to hear from you.