Senior Manager, Data Science and GenAI Lead - Orlando, FL; Hybrid

By combining state-of-the-art data science techniques, cutting‑edge Internet of Things (IoT) technologies, and Software as a Service, we enable a more connected, intelligent and efficient supply chain. We’re creating value from massive, connected data. Our unmatched insights illuminate more than 300,000 supply chains, more than a million customers and partners, and over 300 million physical assets that are constantly on the move around the world.

CHEP is a Brambles / BXB Digital company, the global leader in supply chain logistic solutions operating through the CHEP brand. Brambles Limited is listed on the Australian Securities Exchange (ASX) and has its headquarters in Sydney, Australia. Operating in more than 60 countries, with its largest operations in North America and Western Europe, we employ more than 14,500 people and owns over 550 million pallets, crates and containers through a network of approximately 850 service centres.

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 and GenAI projects are delivered on a timely manner.
• Internal customer satisfaction.
• Quantitative targets for data and analytics initiatives (specific for each project and aligned with Finance objectives).
• Deployment of the data products as per plan.
• Ensure data products and Machine Learning models quality.
• Improve business processes using advanced analytics techniques.

Internal:
Advanced Data & Analytics, Processes Digitalization, Supply Chain, Commercial, Serialization+, Finance, Digital

• Bachelor's degree in Business Administration, Economics, Data Analytics, Computer Science, Information Systems, or a related field.
• MBA or Advanced degree preferred

• Proven experience of 5+ years in Data Science, Software Development, Data Analytics, or related fields, including 3+ years in a managerial capacity.
• Strong understanding of Machine Learning concepts, Data Science, GenAI, and Software Development techniques for data products.
• Extensive knowledge of corporate data sources.
• Demonstrated expertise in Data Science with business focus.
• Experience in project management, including planning, resource allocation, risk management, and stakeholder communication.
• Working on remote teams.