EU Planning Data Analyst

EU Planning Data Analyst

Full-Time 40000 - 60000 £ / year (est.) No home office possible
Fashion Personnel

At a Glance

  • Tasks: Analyse data and support demand planning while improving data systems.
  • Company: Exciting brand focused on creativity, quality, and sustainability.
  • Benefits: Competitive salary, pension scheme, 33 days leave, and hybrid work.
  • Why this job: Join a dynamic team and make a real impact in a growing company.
  • Qualifications: Strong analytical skills, Excel expertise, and interest in modern tools like Python.
  • Other info: Fun and inclusive office environment with great career growth potential.

The predicted salary is between 40000 - 60000 £ per year.

A brilliant opportunity has arisen for a planning data analyst to join a fantastic company, who are going through an exciting period of growth. The brand is dedicated to creativity and quality, focusing also on innovation and sustainability. The brand specialises in a wide variety of products, that prove popular with children and adults.

Key Responsibilities

  • The planning data analyst will support the demand planning team and the supply chain team; acting as a bridge of strong communication and collaboration.
  • You will focus on data analysis, tool building and supporting S&OP, as well as having a mindset of continuously looking to improve data systems, improving spreadsheets and proactively owning data integrity.

Qualifications

  • The ideal candidate will be highly analytical, a super-user of excel, BI tools and of SQL.
  • You will also have a strong understanding of data modelling, have an interest in using modern tools such as Python or AI to assist with tasks.
  • You will have excellent communication skills and the ability to work cross-functionally, influencing and collaborating, to ensure the best outcome for the brand.

Benefits

  • In return, the company offers a salary ranging from £50,000 - £60,000, a pension scheme, 33 days annual leave.
  • This is a hybrid role, based in central London where you will be expected to work from the office three days a week and two from home.
  • The office environment is fun, dynamic and inclusive.

EU Planning Data Analyst employer: Fashion Personnel

Join a vibrant and innovative company that values creativity and sustainability, offering a dynamic work culture in the heart of central London. As an EU Planning Data Analyst, you will benefit from a competitive salary, generous annual leave, and a hybrid working model that promotes work-life balance. With a strong focus on employee growth and collaboration, this is an excellent opportunity to enhance your skills while contributing to exciting projects in a supportive environment.
Fashion Personnel

Contact Detail:

Fashion Personnel Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land EU Planning Data Analyst

✨Tip Number 1

Network like a pro! Reach out to people in the industry, attend events, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.

✨Tip Number 2

Prepare for interviews by practising common questions and showcasing your analytical skills. Be ready to discuss how you've used tools like Excel, BI, or SQL in past roles to solve problems or improve processes.

✨Tip Number 3

Show off your creativity! When discussing your experience, highlight any innovative solutions you've implemented. This aligns perfectly with the brand's focus on creativity and quality.

✨Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in being part of our exciting growth journey.

We think you need these skills to ace EU Planning Data Analyst

Data Analysis
Excel
Business Intelligence (BI) Tools
SQL
Data Modelling
Python
Artificial Intelligence (AI)
Communication Skills
Collaboration
S&OP Support
Data Integrity Management
Tool Building
Problem-Solving Skills
Adaptability

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that match the role of a planning data analyst. Highlight your analytical prowess, Excel super-user status, and any experience with BI tools or SQL. We want to see how you can contribute to our exciting growth!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data analysis and how you can support our demand planning and supply chain teams. Show us your enthusiasm for creativity and innovation in your writing.

Showcase Your Technical Skills: Don’t forget to mention your experience with modern tools like Python or AI. If you've built any tools or improved data systems in the past, share those examples! We love seeing candidates who are proactive about data integrity and continuous improvement.

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 this fantastic opportunity. Plus, it shows us you’re keen to join our dynamic team!

How to prepare for a job interview at Fashion Personnel

✨Know Your Data Tools

Make sure you brush up on your Excel, BI tools, and SQL skills before the interview. Be ready to discuss how you've used these tools in past roles, and think of specific examples where your data analysis made a real impact.

✨Show Your Analytical Mindset

Prepare to demonstrate your analytical thinking during the interview. You might be asked to solve a problem or analyse a dataset on the spot, so practice explaining your thought process clearly and logically.

✨Communicate Effectively

Since this role involves cross-functional collaboration, practice articulating your ideas and findings in a way that’s easy for others to understand. Think about how you can influence and engage with different teams using your communication skills.

✨Emphasise Continuous Improvement

Be ready to discuss how you’ve proactively improved data systems or processes in previous roles. Highlight any experience you have with modern tools like Python or AI, and share your thoughts on how they can enhance data integrity and efficiency.

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