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Company: Newmont
Role: Advanced Analytics Program Leader
Duration: July 2023 - December 2025
Newmont Corporation is the world's largest gold mining company, headquartered in Greenwood Village, Colorado. The company is a leader in sustainability, focusing on environmental and social responsibility.
As the head of the Enterprise Data and Analytics function, I oversee all aspects of customer engagement, strategic planning, solution development, and program management. My role focuses heavily on change management and ensuring the realization of benefits.
Responsibilities
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Managed a $15 million budget and led a global team comprising BI analysts, data scientists, and data engineers.
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Transformed the strategy and culture towards a customer-centric, value-based approach, positioning the organization as a Data and Analytics Center of Excellence (CoE).​
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Established governance and agile-based management practices.
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Collaborated closely with leadership to define and expedite data and analytics roadmaps aligned with operational excellence.
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Led significant initiatives such as the Value Driver Tree Program and the Global Plant Analytics Program, projecting over $10 million in business value.
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Spearheaded multiple POCs for advanced analytics and AI applications to enhance operational efficiencies.
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Fostered cross-functional collaboration across diverse business units to ensure data-driven decision-making and continuous improvement in mining operations.
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Developed and implemented data governance frameworks, ensuring data quality, security, and compliance across all projects and initiatives.
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Mentored and developed talent within the data and analytics teams, creating a culture of innovation and continuous learning.
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Championed integrating emerging technologies, including AI/ML and IoT, into Newmont's operational processes to drive automation and predictive insights.
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Partnered with external vendors and stakeholders to identify cutting-edge solutions and technology partnerships, enhancing Newmont's data and analytics capabilities.
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Led change management efforts, ensuring smooth transitions while implementing new systems, tools, and processes across the organization.
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Provided executive-level reporting and insights on program performance, aligning data and analytics initiatives with overall business objectives and KPIs.
Technologies Utilized
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AWS and Azure Data Ecosystems: Leveraged cloud platforms for scalable data storage, processing, and analytics.
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Power BI and Tableau: Utilized for advanced data visualization and business intelligence reporting.
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SQL, Python, R: Used for data manipulation, analysis, and building machine learning models.
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Microsoft Dynamics 365 CRM and SAP: Managed customer relationships and integrated data from various enterprise systems.
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Snowflake and Databricks: Employed for cloud data warehousing and big data analytics.
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Apache Hadoop and Spark: Processing large-scale data sets and real-time analytics.
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Jupyter Notebooks and Databricks Notebooks: For collaborative data analysis and model development.
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Git/GitHub: For version control and collaborative software development.
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Machine Learning Frameworks: TensorFlow, Keras, and Scikit-learn for building predictive models.