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- Tasks: Analyse data to support customer needs and improve operations.
- Company: Join Maersk, a leader in global logistics with a diverse team.
- Benefits: Inclusive workplace, competitive salary, and opportunities for growth.
- Why this job: Make an impact by driving data-driven decisions in a dynamic environment.
- Qualifications: Experience in data analysis, Excel, and Power BI preferred.
- Other info: Embrace diversity and enjoy a supportive work culture.
The predicted salary is between 35000 - 45000 £ per year.
At Maersk we have a vision that is larger than the ocean: to be a true integrator of container logistics connecting and simplifying our customers' supply chain through global end-to-end solutions. We count on our people to make it happen.
We are looking to recruit a Data Analyst to drive and deliver customer focussed data analysis to support and develop the local operation and customer needs.
Responsibilities- Communicating with internal clients and third parties
- Use of internal systems to provide analysis of trends, risks and opportunities
- Provide expertise, solutioning, leadership, and training in the use of Maersk SCM operating applications / platforms
- Support system implementation / application demonstrations where required
- To provide best practice initiatives seeking out or supporting system efficiencies
- Leading with regular and ad-hoc tasks, depending on the project and customer requirements
- Understanding of agreed customer and internal KPIs and work with the IM Team to ensure results meet or exceed in all areas
- Support financial reporting and capture of operational volumes and productivities
- Support operational data capture and creating relevant analysis documentation for the customer and internal use
- Creating and development of Power BI reports
- Presenting of data analysis to the customer and internal stakeholders
- To communicate with employees and other managers in an effective and respectful manner
- Assist with other clerical and operational duties as and when required
- Attendance of all training programmes provided in line with the needs of the role
- Good working experience in Microsoft Office specifically Excel
- Good knowledge of the relevant WMS
- Experience of working with Power BI reporting
- Ideally in a Warehousing/Logistics environment
- Communication at all levels
- Experience of presenting data analysis to internal and external stakeholders
- Ensure timely and accurate reporting is delivered
- Co-ordination and communication with multiple stakeholders
- Assist in the achievement of customer Key Performance Indicators (KPIs)
Data Analyst in Doncaster employer: A.P. Moller - Maersk
Contact Detail:
A.P. Moller - Maersk Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst in Doncaster
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Maersk on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by practising common data analyst questions. Think about how you can showcase your experience with Power BI and Excel. We want to see how you can turn data into actionable insights!
✨Tip Number 3
Show off your soft skills! Maersk values communication and teamwork, so be ready to share examples of how you've effectively collaborated with others and presented data to stakeholders in the past.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the Maersk team and contributing to their vision.
We think you need these skills to ace Data Analyst in Doncaster
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Analyst role at Maersk. Highlight your experience with data analysis, Power BI, and any relevant logistics or warehousing background. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data analysis and how you can contribute to Maersk's vision. We love seeing enthusiasm and a personal touch in applications.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Microsoft Excel and any experience with WMS systems. We’re looking for someone who can hit the ground running, so make those skills stand out in your application!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details you need about the role and our company culture there!
How to prepare for a job interview at A.P. Moller - Maersk
✨Know Your Data Tools
Make sure you brush up on your skills with Microsoft Excel and Power BI. Be ready to discuss how you've used these tools in past roles, especially in a logistics or warehousing context. Having specific examples of reports you've created or analyses you've conducted will really impress the interviewers.
✨Understand the Company’s Vision
Familiarise yourself with Maersk's mission to connect and simplify supply chains. Think about how your role as a Data Analyst can contribute to this vision. Being able to articulate how your skills align with their goals will show that you're not just looking for any job, but that you're genuinely interested in being part of their team.
✨Prepare for Stakeholder Communication
Since the role involves communicating with internal clients and stakeholders, practice explaining complex data insights in simple terms. You might be asked to present a piece of analysis during the interview, so think about how you would convey your findings clearly and effectively.
✨Showcase Your Problem-Solving Skills
Be ready to discuss how you've identified trends, risks, and opportunities in your previous work. Prepare a couple of scenarios where you provided solutions or efficiencies through your data analysis. This will demonstrate your ability to drive results and support operational needs.