Andrea Aranguren is a highly skilled and results-oriented Senior Data Scientist with 8 years of experience in leveraging machine learning, statistical modeling, and data visualization to drive business insights and product innovation. She has a strong background in developing end-to-end data solutions, from data acquisition and preprocessing to model deployment and performance monitoring. Andrea is passionate about ethical AI and has contributed to projects focusing on fairness and transparency in algorithmic decision-making. She is a proactive collaborator, adept at communicating complex technical findings to both technical and non-technical stakeholders, and thrives in dynamic, fast-paced environments. Andrea is committed to continuous learning and staying at the forefront of advancements in data science and artificial intelligence.
Andrea Aranguren's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Successfully led a team of 4 data scientists to develop and deploy a predictive analytics model that improved customer retention by 18% within the first year of implementation.
Co-authored and published a paper in a reputable journal on 'Mitigating Bias in Machine Learning Models for Financial Services', contributing to industry best practices.
Received an internal company award for developing a novel anomaly detection system that significantly reduced fraudulent transactions by 12%.
Invited as a keynote speaker to present on 'The Future of AI in E-commerce', sharing insights with over 500 industry professionals.
Columbia University - Columbia Business School - Year 2008
University of Pennsylvania - Year 2001
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Minehub Technologies Inc. is an open, enterprise-grade platform for digital trade, bringing efficiency, transparency, and responsibility to global mining and metals supply chains. The platform connects buyers, sellers, financiers, and logistics providers, allowing them to securely exchange information for physical commodity transactions. It aims to streamline post-trade operations, reduce paperwork, and improve data accuracy using technologies like blockchain.
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