Senior Data Scientist
Listed on 2025-12-26
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IT/Tech
Data Analyst, AI Engineer, Machine Learning/ ML Engineer, Data Scientist
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.
Job DescriptionKey Responsibilities May Include:
- Collaborate with key stakeholders to identify business challenges, translating ambiguous problems into structured analyses using statistical modelling and machine learning algorithms.
- Lead the selection, validation, and optimization of models to discover meaningful patterns and insights, ensuring models remain relevant, reliable, and scalable.
- Drive continuous integration and deployment of data science solutions, optimizing performance through advanced machine learning techniques, code reviews, and best practices.
- Develop and deliver sophisticated visualizations, dashboards, and reports, translate complex data into clear, actionable insights for business stakeholders.
- Present technical solutions to business stakeholders, using creative methods to explain complex concepts, increase understanding, and encourage solution adoption.
- Mentor and develop junior data scientists, fostering a culture of continuous learning, knowledge sharing, and skills development within the organization.
- Write clean, high-quality code, ensuring all outputs pass quality assurance checks, and contribute to the development of novel solutions to solve complex business problems.
- Stay informed on industry trends, emerging tools, and techniques, applying them to improve data science practices and encourage innovation within the team.
- Lead strategy development for one or more data products, managing roadmaps, identifying requirements, and collaborating with business stakeholders to ensure alignment with business goals.
Sr. Data Scientist – Any of the location - London/Manchester/Madrid (1 Position)
Position PurposeThe Senior Data Scientist is responsible for designing and developing advanced tools and products that leverage Machine Learning, Data Science, and Generative AI techniques using data sourced from various internal and external platforms. This role focuses on increasing supply chain efficiency, boosting productivity, and delivering measurable value to customers by implementing innovative models, algorithms, and data-driven solutions aligned with business goals.
Major/KeyAccountabilities
- Design, develop, and deploy machine learning models, algorithms, and advanced analytics solutions to improve supply chain efficiency, productivity, and decision-making.
- Leverage data from multiple internal and external sources to build innovative tools and data products that deliver measurable business value.
- Collaborate closely with cross-functional teams including data engineers, product managers, and business stakeholders to align analytics solutions with strategic objectives.
- Ensure data quality, model reliability, and performance by validating datasets and monitoring deployed models.
- Lead and mentor junior data scientists and analysts, fostering skill development and best practices within the team.
- Drive continuous innovation by exploring emerging data science and AI technologies, including generative AI for supply chain applications.
- Communicate insights, risks, and recommendations effectively to both technical and non-technical stakeholders.
- Support prioritization and management of data science work streams to meet delivery timelines and resource allocation.
- Contribute to the creation of business cases by quantifying the impact of data science solutions on supply…
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