Data Science Principal

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.

As the Data Science Team Lead, you will be developing tools and technologies that leverage Data from a variety of sources to increase supply chain efficiencies and provide value to our customer.

• 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.

• Experience in people and/or project management activities.
• Utilized multiple data science methodologies.
• Presented to non-technical audiences.
• Researched and implemented new Data Science techniques.
• Have worked autonomously and delivered results on schedule.

• Degree in Data Science, Computer Science, Engineering, Science, Information Systems and/or equivalent formal training plus work experience.
• BS & 7+ years of work experience.
• MS & 6+ years of work experience.
• Proficient with machine learning and statistics.
• Proficient with Python, deep learning frameworks, Computer Vision, Spark.
• Have produced production level algorithms.
• Proficient in researching, developing, synthesizing new algorithms and techniques.
• Excellent communication skills.

• Master’s or PhD level degree.
• 7+ years of work experience in a data science role.
• Proficient with cloud computing environments, Kubernetes, etc.
• Familiarity with Data Science software & platforms (e.g. Databricks).
• Software development experience.
• Research and new algorithm development experience.

• Demonstrable experience of machine learning techniques and algorithms.
• Experience with statistical techniques and CRISP-DM lifecycle.
• Commercial experience or experimental Jupyter notebooks to production.
• Production ML
  
  Experience:
  
  Deployed models that serve real users, ability of scale to million users without incurring technical debt.
• Strong programming skills in Python and familiarity with ML libraries and frameworks such as Tensor Flow, PyTorch, Scikit-learn, or similar.
• MLOPS experience with tools such as Drift, Decay, A/B Testing. Integration and Differential testing, python package building, code version etc.
• Experience with data pipeline creation and working with structured and unstructured data.
• Familiarity with cloud platforms (AWS, Azure, GCP) and…