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2026-6312 - Master Thesis – Improving Customer Onboarding for Digital Fleet Management

Fri, 09 Oct 2026 13:18:15 Z

Category : Active Jobs/Student Possibilities
Contract type : Student job
Position description :
User Experience (UX) Research & Learning Experience Design At Toyota Material Handling Europe, we create the technology that keeps the world moving. Diverse businesses across Europe depend on our logistics and material handling solutions. By pioneering technology such as automation, connectivity and productivity solutions, we create opportunities for our customers’ logistics operations to be as efficient as possible. We firmly believe in setting ideas in motion. That is why we are investing more than ever in research and development. Our multidisciplinary teams work both conceptually and practically to develop the next generation of material handling products and solutions. By providing our Research and Development organisation with the creative freedom and resources needed to explore new technologies, we aim to stay at the forefront of innovation. At Toyota Material Handling Europe, we contribute to a smarter and more sustainable society, today and tomorrow. Background and purpose Our digital fleet management solutions, My Toyota Material Handling and I_Site, help customers gain insights into their forklift fleets and make informed operational decisions. Today, customers learn to use these tools through several activities, including live onboarding sessions, online training, introductory emails and their first experience with the products. These activities vary between markets, and we need a better understanding of what works well and where customers experience difficulties, receive too much information or feel uncertain when getting started. You will build on existing internal research and focus on a selected part of the onboarding journey. Thesis description You will investigate how customers learn to use our digital tools and explore how we can make the onboarding experience clearer, more consistent and easier to follow. Building on existing research and focusing on a selected part of the onboarding journey, you will: Investigate how customers experience the current onboarding activities. Identify where they encounter difficulties or receive too much information. Develop design principles and propose improvements based on user research and learning design. Create prototypes for one or two selected activities and evaluate them with users. Your findings will provide recommendations for improving customer onboarding across markets.

Your profile Master’s student in Design, UX, Cognitive Science, Human-Computer Interaction or a related field. Interest in user research, digital products, learning design and customer experience. Ability to work with qualitative and quantitative insights and translate them into practical design recommendations. Good English communication skills and the ability to engage with users and stakeholders. Beneficial skills (not mandatory) Experience with interviews, observation or usability testing. Experience with prototyping tools such as Figma or similar. Knowledge of learning design, instructional design or service design.
Location : Gothenburg

2026-6310 - Master Thesis - Estimating Forklift Usage from Low-Frequency CAN Data

Fri, 09 Oct 2026 13:17:31 Z

Category : Active Jobs/Student Possibilities
Contract type : Student job
Position description :
At Toyota Material Handling Europe (TMHE), we create the technology that keeps the world moving. Diverse businesses across Europe depend on our logistics and material handling solutions. By pioneering technology such as automation, connectivity and productivity solutions, we create opportunities for our customers’ logistics operations to be as efficient as possible. We firmly believe in setting ideas in motion. That is why we are investing more than ever in research and development. Our multidisciplinary teams work both conceptually and practically to develop the next generation of material handling products and solutions. By providing our Research and Development organisation with the creative freedom and resources needed to explore new technologies, we aim to stay at the forefront of innovation. At Toyota Material Handling Europe, we contribute to a smarter and more sustainable society, today and tomorrow. Background and purpose How frequently do we need to collect vehicle data to understand how a forklift is being used? Connected forklifts generate large volumes of data through their Controller Area Network (CAN). Collecting data frequently can provide detailed insights into vehicle operation, but it also increases the amount of information that needs to be transmitted and stored. At TMHE, we want to understand how different sampling frequencies affect the reliability of usage estimates, using vehicle speed and travelled distance as an initial case. The purpose of this thesis is to investigate how reducing the amount of collected data affects estimation accuracy, and whether statistical and machine learning methods can extract reliable information from sparsely sampled vehicle data. The results can provide a foundation for future data-driven applications, such as usage prediction and predictive maintenance. Thesis description Working with recorded vehicle data, you will investigate how reducing the sampling frequency affects the accuracy of travelled-distance estimates. Your work will include: Analyse vehicle speed data and establish a method for predicting total travelled distance based on limited samples. Investigate whether statistical methods or machine learning can improve estimates when fewer data points are available. Evaluate how different sampling frequencies influence estimation accuracy. Recommend suitable sampling approaches based on the results and the trade-off between accuracy and data requirements. The expected outcome is an evidence-based assessment of how much data is needed to estimate travelled distance reliably, together with recommendations for future data collection.

Your profile We are looking for Master’s students studying: Data Science or Computer Science Machine Learning or a related field Applied Mathematics or Statistics Electrical Engineering or Signal Processing You enjoy working with real-world datasets and have experience with programming for data analysis. You have an analytical approach to problem-solving and can evaluate and communicate technical findings clearly in English. Beneficial skills (not mandatory) Knowledge of time-series analysis or statistical estimation. Experience with signal processing, data visualisation or machine learning. Familiarity with connected vehicles, telemetry or CAN data.
Location : Linköping

2026-6311 - Master Thesis – Improving the Use of Digital Mock-Ups in Mechanical Product Development

Fri, 09 Oct 2026 13:16:56 Z

Category : Active Jobs/Student Possibilities
Contract type : Student job
Position description :
At Toyota Material Handling Europe (TMHE), we create the technology that keeps the world moving. Diverse businesses across Europe depend on our logistics and material handling solutions. By pioneering technology such as automation, connectivity and productivity solutions, we create opportunities for our customers’ logistics operations to be as efficient as possible. We firmly believe in setting ideas in motion. That is why we are investing more than ever in research and development. Our multidisciplinary teams work both conceptually and practically to develop the next generation of material handling products and solutions. By providing our Research and Development organisation with the creative freedom and resources needed to explore new technologies, we aim to stay at the forefront of innovation. At Toyota Material Handling Europe, we contribute to a smarter and more sustainable society, today and tomorrow. Background and purpose How can digital mock-ups support better decisions earlier in mechanical product development? As mechanical products become increasingly complex, engineers need to evaluate design alternatives, identify potential issues and share technical information throughout the development process. Digital mock-ups allow teams to visualise and review products before physical hardware is available. However, we want to better understand how these tools are used in practice, where they create value and what limits their effectiveness. The purpose of this thesis is to investigate how the use of digital mock-ups can be improved to support collaboration and early engineering decisions. Thesis description Working with engineers and existing product development practices, you will: Investigate how digital mock-ups are currently used in selected mechanical design and review activities. Identify challenges related to information sharing, collaboration and early design decisions. Explore relevant methods and opportunities to improve the use of digital mock-ups throughout the development process. Develop practical, research-based recommendations for future ways of working. Your findings will provide a foundation for improving engineering workflows, potentially including a process proposal or prioritised roadmap. The thesis is not expected to deliver a production-ready digital system.

Your profile We are looking for two Master’s students studying: Mechanical Engineering Product Development or Product Design Engineering Industrial Engineering and Management A related engineering field You have an interest in mechanical design, digital engineering and product development processes. You enjoy analysing technical challenges, collaborating with engineers and translating findings into practical recommendations. You can communicate your results clearly in English. Beneficial skills (not mandatory) Familiarity with Computer-Aided Design (CAD) and 3D modelling. Knowledge of digital mock-ups (DMU), design reviews or Product Lifecycle Management (PLM). Experience with engineering analysis, interviews or process mapping.
Location : Linköping

2026-6313 - Master Thesis – Improving Wireless Communication for Autonomous Forklifts

Fri, 09 Oct 2026 13:16:25 Z

Category : Active Jobs/Student Possibilities
Contract type : Student job
Position description :
At Toyota Material Handling Europe (TMHE), we create the technology that keeps the world moving. Diverse businesses across Europe depend on our logistics and material handling solutions. By pioneering technology such as automation, connectivity and productivity solutions, we create opportunities for our customers’ logistics operations to be as efficient as possible. We firmly believe in setting ideas in motion. That is why we are investing more than ever in research and development. Our multidisciplinary teams work both conceptually and practically to develop the next generation of material handling products and solutions. By providing our Research and Development organisation with the creative freedom and resources needed to explore new technologies, we aim to stay at the forefront of innovation. At Toyota Material Handling Europe, we contribute to a smarter and more sustainable society, today and tomorrow. Background and purpose How can autonomous forklifts maintain reliable wireless communication in constantly changing warehouse environments? Autonomous forklifts rely on wireless connectivity for functions such as mission execution, fleet management and diagnostics. However, metal racking, moving vehicles and changing loads can affect radio conditions and lead to communication interruptions together with limited opportunities to modify existing network infrastructure. At TMHE, we want to investigate whether predicting communication quality and adapting the forklift's antenna configuration could improve reliability. The purpose of this thesis is to evaluate the technical potential and practical feasibility of such an approach. Thesis description Working with our Research & Innovation team, you will investigate how adaptive antenna techniques could improve wireless communication in warehouse environments. Together with your mentor, you will define a suitable technical scope and: Investigate how changing warehouse conditions affect wireless communication and explore methods for predicting communication quality. Select and develop a promising approach, such as antenna selection or adjusting antenna orientation or position. Evaluate the approach through simulation, experiments or a prototype, depending on the agreed scope and available equipment. Compare the results with a conventional antenna setup and assess potential benefits against added system complexity. Your findings will help determine whether adaptive antenna technology offers a promising direction for future development of autonomous forklifts.

Your profile We are looking for one or two Master’s students studying: Electrical Engineering Communication Systems or Wireless Communications Engineering Physics or a related field You have an interest in wireless communication, radio systems and technical problem-solving. You enjoy combining theoretical analysis with practical evaluation and can communicate your findings clearly in English. Beneficial skills (not mandatory) Experience Knowledge of signal processing, antenna theory or wireless communication systems. Experience with MATLAB, simulation tools or experimental design. Familiarity with data analysis or communication performance evaluation. Previous experience with autonomous forklifts is not required.
Location : Linköping

2026-6309 - Master Thesis – Digital Thread for Product Development: PLM & CAD

Fri, 09 Oct 2026 13:15:51 Z

Category : Active Jobs/Student Possibilities
Contract type : Student job
Position description :
At Toyota Material Handling Europe (TMHE), we create the technology that keeps the world moving. Diverse businesses across Europe depend on our logistics and material handling solutions. By pioneering technology such as automation, connectivity and productivity solutions, we create opportunities for our customers’ logistics operations to be as efficient as possible. We firmly believe in setting ideas in motion. That is why we are investing more than ever in research and development. Our multidisciplinary teams work both conceptually and practically to develop the next generation of material handling products and solutions. By providing our Research and Development organisation with the creative freedom and resources needed to explore new technologies, we aim to stay at the forefront of innovation. At Toyota Material Handling Europe, we contribute to a smarter and more sustainable society, today and tomorrow. Background and purpose How can we ensure that engineers have access to the right information throughout product development? Engineering data is often distributed across different systems, files and teams. When information is difficult to access or trace, understanding design changes, reusing existing knowledge and making informed technical decisions become more challenging. A digital thread connects information across the product lifecycle, making it easier to understand how engineering data relates to different products, processes and decisions. A key principle is to establish a reliable single source of truth, where engineers can access consistent and authoritative information regardless of where the data is created or managed. At TMHE, we want to explore how product lifecycle management (PLM) and computer-aided design (CAD) can support a more connected and traceable flow of engineering information. The purpose of this thesis is to develop a digital thread concept based on our existing engineering processes and identify opportunities for improvement. Thesis description Working with a selected part of our R&D product development process, you will: Map how engineering information is created, shared and managed across relevant systems and teams. Identify gaps in information traceability, accessibility, ownership and reuse. Explore how PLM and CAD approaches could improve the connection between engineering data and development activities. Develop a future-state digital thread concept and recommend priorities for further development. Your findings will provide a research-based concept and practical recommendations to guide future decisions. The thesis does not involve implementing a new PLM or CAD platform.

Your profile We are looking for two Master’s students studying: Mechanical Engineering or Product Development Industrial Engineering and Management Information Systems or a related engineering field You have an interest in digital engineering, product development and how information systems support technical processes. You enjoy analysing complex problems, collaborating with different stakeholders and translating your findings into clear recommendations. You can communicate effectively in English. Beneficial skills (not mandatory) Familiarity with CAD, PLM or product data management (PDM). Experience with process mapping, systems analysis or technical information management. An interest in engineering data, information traceability or digital transformation. Previous professional experience with PLM systems is not required.
Location : Linköping

2026-6314 - Master Thesis – Machine Learning for Component Cost Estimation

Fri, 09 Oct 2026 13:15:20 Z

Category : Active Jobs/Student Possibilities
Contract type : Student job
Position description :
At Toyota Material Handling Europe (TMHE), we create the technology that keeps the world moving. Diverse businesses across Europe depend on our logistics and material handling solutions. By pioneering technology such as automation, connectivity and productivity solutions, we create opportunities for our customers’ logistics operations to be as efficient as possible. We firmly believe in setting ideas in motion. That is why we are investing more than ever in research and development. Our multidisciplinary teams work both conceptually and practically to develop the next generation of material handling products and solutions. By providing our Research and Development organisation with the creative freedom and resources needed to explore new technologies, we aim to stay at the forefront of innovation. At Toyota Material Handling Europe, we contribute to a smarter and more sustainable society, today and tomorrow. Background and purpose Can machine learning help engineers estimate component costs more accurately and efficiently? Cost estimation plays an important role in product development, influencing engineering, planning and sourcing decisions. Today, the process relies heavily on manual spreadsheets and expert knowledge, making it time-consuming and challenging to apply consistently. At TMHE, we want to investigate whether historical product and cost data can provide a foundation for data-driven estimation. The purpose of this thesis is to evaluate the potential of machine learning to support cost estimation while maintaining transparency and engineering judgement. Thesis description Working with historical article and cost data, you will investigate how machine learning could support engineering cost estimation. Your work will include: Analyse the available data and identify relevant cost drivers and potential limitations. Investigate and develop suitable machine learning approaches for cost prediction. Evaluate the results against existing estimation methods, considering accuracy and interpretability. Develop a proof of concept and recommend how the approach could support future engineering processes. The outcome will provide an evidence-based assessment of the feasibility and potential value of machine learning for cost estimation.

Your profile We are looking for two Master’s students studying: Data Science or Machine Learning (ML) Computer Science or Artificial Intelligence (AI) Applied Mathematics or Statistics Industrial Engineering or a related field with relevant machine learning experience You have a strong interest in applying data-driven methods to real engineering challenges and experience with programming for data analysis, preferably in Python. You approach problems analytically, enjoy experimenting with different solutions and can communicate technical findings clearly in English. Beneficial skills (not mandatory) Experience with machine learning libraries such as scikit-learn. Familiarity with regression models, feature engineering or model evaluation. Knowledge of product development, manufacturing or engineering cost estimation.
Location : Linköping

2026-6315 - Master Thesis – Net-Zero Strategy & Carbon Management

Fri, 09 Oct 2026 13:14:40 Z

Category : Active Jobs/Student Possibilities
Contract type : Student job
Position description :
At Toyota Material Handling Europe (TMHE), we create the technology that keeps the world moving. Diverse businesses across Europe depend on our logistics and material handling solutions. By pioneering technology such as automation, connectivity and productivity solutions, we create opportunities for our customers’ logistics operations to be as efficient as possible. Background and purpose How can an international industrial company turn ambitious climate targets into measurable progress? TMHE has set science-based targets, validated by the Science Based Targets initiative (SBTi), to achieve net-zero greenhouse gas emissions across our value chain by fiscal year 2041, using fiscal year 2023 as our baseline. Achieving these targets requires more than setting ambitions. We need reliable emissions data, effective decarbonisation measures and management approaches that support informed decisions across our operations and value chain. The purpose of this thesis is to investigate a specific challenge within our net-zero programme and develop recommendations that support its continued development. Thesis description You will work with one of three potential focus areas, with the final scope agreed together with your mentor: Net-zero strategy and SBTi: Investigate how evolving science-based target standards could influence our approach to implementing and managing our net-zero commitments. Scope 2 decarbonisation: Explore approaches to reducing emissions associated with purchased energy and identify opportunities for improving our Scope 2 strategy. Scope 3 data management: Investigate how we can improve the quality, availability and management of emissions data across our value chain. Combining academic research, relevant external examples and insights from our organisation, you will assess the selected challenge and develop evidence-based recommendations. Your findings should provide practical next steps that can support future decisions within TMHE's net-zero programme.

Your profile We are looking for one or two Master's students studying: Sustainability Engineering and Management Environmental Engineering or Environmental Science Industrial Ecology Industrial Engineering and Management Energy Systems or a related field You have a strong interest in corporate sustainability, decarbonisation and how environmental analysis can support business decisions. You enjoy working analytically, can approach complex problems in a structured way and communicate your findings clearly in English. Beneficial skills (not mandatory) Knowledge of greenhouse gas accounting, including the GHG Protocol or Scope 1, 2 and 3 emissions. Familiarity with climate targets, sustainability frameworks or environmental management. Experience with data analysis, environmental assessment or business case development.
Location : Linköping

2026-6316 - Master Thesis – Tyre–Floor Friction Estimation for Autonomous Forklifts

Fri, 09 Oct 2026 13:14:11 Z

Category : Active Jobs/Student Possibilities
Contract type : Student job
Position description :
At Toyota Material Handling Europe (TMHE), we create the technology that keeps the world moving. Diverse businesses across Europe depend on our logistics and material handling solutions. By pioneering technology such as automation, connectivity and productivity solutions, we create opportunities for our customers’ logistics operations to be as efficient as possible. We firmly believe in setting ideas in motion. That is why we are investing more than ever in research and development. Our multidisciplinary teams work both conceptually and practically to develop the next generation of material handling products and solutions. By providing our Research and Development organisation with the creative freedom and resources needed to explore new technologies, we aim to stay at the forefront of innovation. At Toyota Material Handling Europe, we contribute to a smarter and more sustainable society, today and tomorrow. Background and purpose How can an autonomous forklift determine how much traction is available while driving? The ability of an autonomous forklift to stop safely depends partly on the friction between its tyres and the floor. As floor conditions change, so can the vehicle's braking performance. Autonomous forklifts use protective fields to detect people and initiate safety-related responses. These fields influence how the vehicle operates and can affect productivity. At TMHE, we want to investigate whether existing vehicle signals, such as wheel speed and localisation data, could provide useful information about available traction and braking capability. The purpose of this thesis is to evaluate the feasibility of friction estimation during operation and explore its potential relevance for future personnel protection concepts. Thesis description Working with our Research & Innovation team, you will investigate how vehicle data could be used to estimate tyre–floor friction. Your work will include: Explore methods for detecting wheel slip and estimating available traction using existing vehicle signals. Investigate under which operating conditions friction or braking capability can be estimated reliably. Use modelling, data analysis or simulation to explore the implications for future personnel protection concepts. Develop recommendations for further research, including technical limitations and safety validation requirements. The expected outcome is a feasibility assessment and recommendations for further development, not a validated safety function or an approved change to protective fields.

Your profile We are looking for two Master’s students studying in at least one of the following fields: Mechanical Engineering, with a focus on vehicle dynamics or mechatronics Automatic Control or Control Engineering Robotics and Autonomous Systems Computer Science or a related field with relevant experience in modelling or control systems You have an interest in vehicle dynamics, autonomous systems and safety-related engineering. You thrive solving technical problems, working with mathematical models and analysing results critically. You can communicate your findings clearly in English. Beneficial skills (not mandatory) Experience with MATLAB, Simulink, Python or similar tools for modelling and simulation. Knowledge of system identification, sensor fusion or signal processing. Familiarity with vehicle dynamics, traction or braking systems.
Location : Linköping

2026-6323 - Master Thesis – AI for Project Management in Product Development

Fri, 09 Oct 2026 13:09:13 Z

Category : Active Jobs/Student Possibilities
Contract type : Student job
Position description :
At Toyota Material Handling Europe (TMHE), we create the technology that keeps the world moving. Diverse businesses across Europe depend on our logistics and material handling solutions. By pioneering technology such as automation, connectivity and productivity solutions, we create opportunities for our customers’ logistics operations to be as efficient as possible. We firmly believe in setting ideas in motion. That is why we are investing more than ever in research and development. Our multidisciplinary teams work both conceptually and practically to develop the next generation of material handling products and solutions. By providing our Research and Development organisation with the creative freedom and resources needed to explore new technologies, we aim to stay at the forefront of innovation. At Toyota Material Handling Europe, we contribute to a smarter and more sustainable society, today and tomorrow. Background and purpose How can artificial intelligence (AI) help project managers make better use of information and focus on the decisions that matter? Product development projects involve complex schedules, resources, technical dependencies and risks. Project managers rely on information from multiple sources to monitor progress, anticipate challenges and make informed decisions. At TMHE, we want to investigate where AI could add value to our project management processes and which applications are worth pursuing. The purpose of this thesis is to identify and evaluate relevant AI opportunities within our R&D Project Management Office (PMO), providing a research-based foundation for future development. Thesis description Working with our PMO and drawing on academic research, existing processes and stakeholder insights, you will: Analyse selected project management workflows and identify challenges where AI could provide support. Investigate relevant AI applications and assess their potential benefits, feasibility and limitations. Evaluate and prioritise potential use cases based on business value, data availability and implementation considerations. Develop recommendations and, if feasible, a concept or proof of concept for one selected use case. Your findings will help us understand where AI could create value and how potential applications could be introduced responsibly into our project management practices.

Your profile We are looking for one or two Master’s students studying: Industrial Engineering and Management Project Management or Innovation Management Computer Science or AI Product Development or a related field You have an interest in the intersection of technology, business processes and project management. You approach complex problems analytically, enjoy collaborating with different stakeholders and can translate research findings into clear recommendations. Good communication skills in English are essential. Beneficial skills (not mandatory) Knowledge of project management methods or product development processes. Familiarity with AI applications, business process analysis or digital transformation. Experience with qualitative research, data analysis or prototyping.
Location : Linköping

2026-6141 - Rental Customer Service - Team Leader

Wed, 16 Sep 2026 22:17:44 Z

Category : Active Jobs/Office/ Administration
Contract type : Permanent
Position description :
We're looking for a Rental Customer Service Team Leader to lead our Short Term Rental team, ensuring exceptional service delivery while supporting business growth and customer satisfaction. What You'll Be Doing: As the Rental Customer Service Team Leader, you'll be responsible for leading and developing a customer service team while ensuring the smooth operation of our Short Term Rental services. Key responsibilities include: Leading, coaching and developing team members through regular reviews, performance conversations and team meetings. Managing all incoming Short Term Rental enquiries and requests. Processing rental orders accurately using established systems and procedures. Managing credits, invoicing and administrative processes to maintain excellent financial control. Working closely with internal stakeholders to ensure accurate fleet planning and utilisation. Monitoring rental fleet performance, pricing and utilisation, identifying opportunities to maximise profitability. Supporting the development of new rental business opportunities and market growth. Ensuring customer issues, fleet damage and field-based concerns are managed effectively and in line with company policy. Overseeing the administration of demo and trial fleets and ensuring off-hired units are collected promptly. Driving achievement of operational KPIs and maintaining a customer-first culture across the team.

We're looking for an inspiring leader who combines strong customer service expertise with excellent organisational and communication skills. You'll ideally have: Proven leadership capability with the ability to motivate, develop and support a high-performing team. Strong interpersonal and relationship-building skills. Excellent organisational, planning and self-management abilities. A customer-first mindset with high levels of integrity, empathy and accountability. Experience working with invoicing, credits, customer queries and financial administration. Good knowledge of customer relationship management principles. Strong Microsoft Office skills. A collaborative approach and the ability to work effectively with multiple stakeholders.
Location : Leicester

2026-6082 - Customer Support Advisor / Administrator

Mon, 31 Aug 2026 22:16:50 Z

Category : Active Jobs/Office/ Administration
Contract type : Fixed-term/Temporary
Position description :
We are looking for a temporary Customer Support Advisor to work within our customer support team in Warrington to provide high quality administration support to customers. About the role The role involves providing first line support for customers within our sales and service operations. Customer Support Advisors will provide overall support but will have a focus on one of our key business areas. On a day-to-day basis this is what you would be doing: Responding to a high volume of customer calls including breakdowns. High quality administration support to internal departments and customers Respond efficiently to all customer enquires Update customer and supplier portals and monitor activity Update activity reports as required Provide quotations to customers as required Support for your focus business area

Here is a quick tick list for the other skills we are looking for: Excellent written and verbal communication skills Excellent time management skills and ability to react quickly to requests Ability to follow company health and safety procedures
Location : Warrington

2026-6095 - Customer Support Advisor / Administrator

Tue, 18 Aug 2026 22:17:27 Z

Category : Active Jobs/Office/ Administration
Contract type : Fixed-term/Temporary
Position description :
We are looking for a part time, temporary Customer Support Advisor to work within our customer support team in Warrington to provide high quality administration support to customers. About the role The role involves providing first line support for customers within our sales and service operations. Customer Support Advisors will provide overall support but will have a focus on one of our key business areas. On a day-to-day basis this is what you would be doing: Responding to a high volume of customer calls including breakdowns. High quality administration support to internal departments and customers Respond efficiently to all customer enquires Update customer and supplier portals and monitor activity Update activity reports as required Provide quotations to customers as required Support for your focus business area

Here is a quick tick list for the other skills we are looking for: Excellent written and verbal communication skills Excellent time management skills and ability to react quickly to requests Ability to follow company health and safety procedures
Location : Warrington