Pedro Tavares

Lead Data Scientist @Glencore

Toronto, ON, CA
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Mar 2024 — Present

Lead Data Scientist @Glencore

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Toronto, ON, CA

Data Scientist Lead in the Group Internal Audit and Assurance actively working with the digitalization of the function through AI and data analytics initiatives.Led a global consulting advisory engagement within Glencore (at corporate and department level) to understand the level of AI adoption within the business and to provide insights and recommendations to senior management in the development of AI governance framework (e.g, AI risk management processes and AI system development lifecycle). Received outstanding feedback from Glencore senior management and key outputs of the engagement has helped Glencore to shape its AI journey. Managed directly 3 people (2 data scientists and 1 IT auditor).Led the development of the end-to-end Data Analytics operating model within the Group Internal Audit and Assurance function including procedures of DA support to audit planning (e.g, annual risk assessments, DA integrated within annual audit plan) and execution (DA involvement within the audit engagements) methodologies. Managed directly 3 data scientists.Data Analytics Lead within audit engagements across different industrial operations, trading and IT (emerging technologies) areas.

EDUCATION

2014 — 2015

University of Arizona

Graduate topics on Artificial Intelligence

2010 — 2018

Universidade Federal de Minas Gerais

Bachelor of Engineering - BE

2022 — 2024

Pontificia Universidad Católica de Chile

Master of Science - MS

ABOUT PEDRO TAVARES

Passionate about solving complex problems with elegant solutions through the use of data. Life long learner striving for continuous improvement. Working with internal audit and assurance with experience in industrial operations, trading and IT audits. Advisor on AI governance and risk management.10+ years working with data science, technology and consulting with broad international work experience in mining and manufacturing industries.Co-author of OpenEnsemble framework, a Python toolkit for performing and analyzing ensemble clustering (machine learning) on complex datasets. Paper published on Journal of Machine Learning Research (USA, 2018).Fluent English and Spanish. Native Portuguese.

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