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- Tasks: Analyse booking data to boost logistics efficiency and enhance courier experience.
- Company: A leading logistics tech company based in Shoreditch.
- Benefits: Competitive salary, flexible remote work, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact on last-mile logistics.
- Qualifications: 3+ years of data analysis experience and strong SQL skills required.
- Other info: On-site role with some remote flexibility in a vibrant work environment.
The predicted salary is between 36000 - 60000 £ per year.
A logistics technology company is looking for a Data Analyst to work on their Last-Mile Marketplace. This role involves analyzing booking data to improve logistics efficiency and enhance courier experience.
Candidates should have at least 3 years of experience in data analysis, strong SQL skills, and effective communication abilities.
Work is primarily on-site in Shoreditch with some remote flexibility.
Data Analyst — Last‑Mile Marketplace Analytics in London employer: Relay Technologies
Contact Detail:
Relay Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst — Last‑Mile Marketplace Analytics in London
✨Tip Number 1
Network like a pro! Reach out to people in the logistics and data analysis fields on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your SQL skills! Prepare a mini-project or case study that highlights your data analysis prowess. Bring it up during interviews to impress the hiring team.
✨Tip Number 3
Practice your communication skills. Being able to explain complex data insights in simple terms is key. Try explaining your past projects to friends or family to get comfortable.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Data Analyst — Last‑Mile Marketplace Analytics in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your data analysis experience, especially with SQL. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Data Analyst position and how your background makes you a perfect fit for our Last-Mile Marketplace team.
Showcase Your Communication Skills: Since effective communication is key in this role, consider including examples of how you've successfully conveyed complex data insights in the past. We love seeing candidates who can bridge the gap between data and decision-making!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Relay Technologies
✨Know Your Data Tools
Make sure you brush up on your SQL skills before the interview. Be ready to discuss specific projects where you've used SQL to analyse data and improve processes. This will show that you not only have the technical skills but also know how to apply them in real-world scenarios.
✨Understand the Last-Mile Challenge
Research the logistics industry, particularly the last-mile delivery challenges. Familiarise yourself with common issues and potential solutions. This knowledge will help you demonstrate your understanding of the role and how you can contribute to enhancing courier experiences.
✨Prepare for Scenario Questions
Expect questions that ask you to solve hypothetical problems related to data analysis in logistics. Practice articulating your thought process clearly and logically. Use the STAR method (Situation, Task, Action, Result) to structure your answers effectively.
✨Showcase Your Communication Skills
Since effective communication is key in this role, be prepared to explain complex data insights in simple terms. Think of examples where you've successfully communicated findings to non-technical stakeholders. This will highlight your ability to bridge the gap between data and decision-making.