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 .
Job Description
You’ll be responsible for managing, developing, and inspiring a high-performing team of data scientists, machine learning engineers, and Generative AI developers. Operating within a squad model, the role focuses on fostering technical excellence across the team by ensuring the quality, scalability, and integrity of their output, rather than directly directing the work.
You’ll work closely with our Head of Global Data & Analytics & Head of Data Science to establish best practices, provide technical oversight, and act as a guardian of quality assurance across all Advanced Analytics projects and deliverables. You will also play a key role in enabling innovation, supporting professional growth, and aligning the team’s capabilities with organisational goals.
By fostering a culture of collaboration, curiosity, and technical rigour, you’ll ensure that the team is empowered to deliver impactful solutions that drive business outcomes and create value.
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Key Responsibilities May Include:
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.
Major/Key Accountabilities
Team Management & Leadership
Foster Team Excellence: Lead and manage a multidisciplinary team of data scientists, machine learning engineers, and GenAI developers, ensuring they are empowered to deliver high-quality, scalable solutions.
Quality Assurance: Establish and enforce best practices for coding, model development, and deployment processes to ensure all outputs meet organisational standards.
Performance Management: Conduct regular 1:1s, performance reviews, and provide constructive feedback to support individual and team growth.
Collaboration: Act as a bridge between squads and stakeholders, ensuring alignment and collaboration across teams to maximise impact.
Upskilling: Develop and execute training plans to enhance the team’s technical capabilities
Mentorship: Provide technical mentorship and career guidance to team members, fostering a culture of continuous learning and professional development.
Knowledge Sharing: Encourage and facilitate the sharing of knowledge, tools, and techniques within the team and across the organisation.
Advanced Analytics Strategy
Strategic Alignment: Contribute to the development and execution of the organisation’s advanced analytics strategy, ensuring alignment with business objectives.
Innovation: Identify and drive opportunities for applying advanced analytics, machine learning, and Generative AI to solve complex business challenges.
Roadmap Development: Collaborate with stakeholders to define and prioritise the roadmap for analytics initiatives, balancing innovation with delivery timelines.
Emerging Trends: Stay ahead of industry trends and emerging technologies, assessing their relevance and potential impact on the organisation.
Operational Excellence
Scalability: Ensure the team’s processes, tools, and solutions are scalable and can support organisational growth.
Data Governance: Champion robust data governance practices, ensuring compliance with legal, ethical, and organisational standards in all analytics initiatives.
Metrics and Impact: Establish and monitor KPIs to measure the team’s performance and the business impact of advanced analytics solutions.
Experience
7+ years’ leadership experience leading, managing or influencing multiple functions, geographies and stakeholders (ideally in a Global Digital Program). Experience managing a large, multi-cultural, diverse team.
Significant previous experience creating and leading cross functional and multi-country business change programmes.
Familiarity with modern data science tools and technologies such as continuous integration, build, deliver, test-driven development and automated acceptance testing.
Experience of managing a portfolio of programmes and initiatives within a matrix structure, creating/delivering customer value propositions, and leading technology related programmes
Skills and Knowledge
Communicating and inspiring confidence at a senior level with technical and non-technical audiences, with the ability to shape strong presentations and narratives that influence and commit people to change.
Experience in multi-facility, international organisations with diverse multi-cultural, corporate cultures.
Strong team engagement and motivation skills. You’ll be adaptable and able to pivot in a dynamic environment, a digital enthusiast, a coach and a communicator.
Ability to lead in a matrix and build capabilities in global teams.
An advocate and ambassador of the ‘test, learn, build or pivot’ approach.
Excellent understanding of machine learning techniques and algorithms.
Knowledge of implementing Data Science, Machine Learning and GenAI solutions at scale.
Experience with common statistical techniques and data science toolkits.
Strong quantitative and analytical skills and experience with data visualisation tools.
Applied statistics skills, such as distributions, statistical testing, regression etc.
Experience with AWS, Databricks and Dataiku.
Strong understanding of data structures and algorithms plus solution and technical design.
Able to quickly pick up new programming languages, technologies, and frameworks
Strong knowledge of applied data science.
Significant expertise in machine learning algorithms and data science methods.
Strong data wrangling experience with structured and unstructured data
Experience with various programming and scripting languages, databases, processing and storage frameworks plus coverage with various hyperparameter tuning approaches
Understanding and experience with CRISP-DM and Agile data science framework
Ability to identify and resolve both people and process related issues
Qualifications
Essential Qualifications:
Bachelor’s Degree in Computer Science, Statistics or equivalent Technical Degrees
Desirable Qualifications:
Agile (SCRUM) Certification
Development Coach Certification
Remote Type
Hybrid Remote
Skills to succeed in the role
Bitbucket, Cloud Infrastructure (Aws), Coaching, Code Reviews, Collaboration, Databricks Platform, Data Science, Data Storytelling, Disruptive Thinking, Feedback, Git, Inclusive Leadership, Leading Change, Leading Customer Centric Teams, Machine Learning (ML), Mentorship, Motivating Teams, Prioritization, Python (Programming Language), Self-Awareness, SQL Tools
We are an Equal Opportunity Employer, and we are committed to developing a diverse workforce in which everyone is treated fairly, with respect, and has the opportunity to contribute to business success while realizing his or her potential. This means harnessing the unique skills and experience that each individual brings and we do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state, or local protected class.
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