Senior Manager, Data Science and GenAI Lead

CHEP helps move more goods to more people, in more places than any other organization on earth via our 347 million pallets, crates and containers. We employ approximately 13,000 people and operate in 60 countries. Through our pioneering and sustainable share-and-reuse business model, the world’s biggest brands trust us to help them transport their goods more efficiently, safely and with less environmental impact.

What does that mean for you? You’ll join an international organization big enough to take you anywhere, and small enough to get you there sooner. You’ll help change how goods get to market and contribute to global sustainability. You’ll be empowered to bring your authentic self to work and be surrounded by diverse and driven professionals. And you can maximize your work-life balance and flexibility through our Hybrid Work Model.

• Lead a team of data scientists, providing mentorship and guidance on daily tasks, fostering professional development and capability growth.
• Oversee the implementation of Continuous Integration/Continuous Deployment (CI/CD) pipelines, ensuring deliverables meet project milestones and quality standards.
• Apply advanced machine learning, forecasting, and statistical analysis techniques to drive experimentation and innovation on data science projects.
• Lead the experimentation and implementation of new data science techniques for projects, ensuring alignment with internal and external customer objectives.
• Communicate project status, methodologies, and results to both technical teams and business stakeholders, translating complex data insights into actionable strategies.
• Facilitate data science team discussions, providing technical expertise on current methods and guiding decision‑making for optimal outcomes.
• Contribute to strategic data science initiatives, influencing the direction of key projects and aligning team efforts with broader business goals.
• Encourage collaboration across teams and functions to ensure seamless integration of data science solutions into business processes and technology platforms.

Lead and mentor a team of data scientists, driving capability development and overseeing project collaborations across teams to ensure successful execution of data science initiatives.

Apply advanced data science methodologies, including machine learning and statistical analysis, to deliver impactful solutions for both internal and external stakeholders.

Foster a culture of continuous learning and innovation, contributing to strategic data science initiatives that align with business goals.

• All Machine Learning models for Advanced D&A Americas.
• All data products initiatives for Advanced D&A Americas.
• All GenAI initiatives for Advanced D&A Americas.

• Lead a team of data scientists, providing mentorship and guidance on daily tasks, fostering professional development and capability growth.
• Oversee the implementation of Continuous Integration/Continuous Deployment (CI/CD) pipelines, ensuring deliverables meet project milestones and quality standards.
• Apply advanced machine learning, forecasting, and statistical analysis techniques to drive experimentation and innovation on data science projects.
• Lead the experimentation and implementation of new data science techniques for projects, ensuring alignment with internal and external customer objectives.
• Communicate project status, methodologies, and results to both technical teams and business stakeholders, translating complex data insights into actionable strategies.
• Facilitate data science team discussions, providing technical expertise on current methods and guiding decision‑making for optimal outcomes.
• Contribute to strategic data science initiatives, influencing the direction of key projects and aligning team efforts with broader business goals.
• Encourage collaboration across teams and functions to ensure seamless integration of data science solutions into business processes and technology platforms.

• Ensure Machine Learning models developed cover business needs.
• Ensure Machine Learning models and GenAI projects are delivered on a timely manner.
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