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- Tasks: Lead a team of 12 in customer analytics and data science initiatives.
- Company: Join a high-growth fashion retailer focused on customer insight and personalization.
- Benefits: Enjoy a hybrid work model and a competitive salary of £110,000 to £120,000.
- Why this job: Make a real impact in a dynamic industry while managing innovative projects.
- Qualifications: Strong experience in customer analytics and proven team management skills required.
- Other info: Position based in Liverpool with flexible office days.
The predicted salary is between 110000 - 120000 £ per year.
We are looking for someone with strong Customer Analytics experience and a proven track record of managing Data Science teams or functions.
As the Head of Analytics & Data Science, you will manage a matrix team of 12 professionals across customer, loyalty, and trading analytics, as well as lead a team of Data Scientists. You will spearhead initiatives related to promotional sales, stock replenishment, weather models, and funnel pipeline optimization. We expect you to have considerable experience in customer analytics and data science, alongside your ability to manage both team members and stakeholders effectively.
Description
We are a high-growth fashion retailer and are excited to find a candidate who will lead all activities related to customer insight and personalization. This position is based in Liverpool with a hybrid work model (3 days a week in the office) and offers a competitive salary ranging from £110,000 to £120,000.
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Head of Analytics & Data Science employer: Workonblockchain
Contact Detail:
Workonblockchain Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Analytics & Data Science
✨Tip Number 1
Make sure to showcase your leadership skills in analytics and data science. Highlight any experience you have in managing teams, especially in a matrix structure, as this is crucial for the role.
✨Tip Number 2
Familiarize yourself with the latest trends in customer analytics and data science. Being able to discuss current methodologies and tools will demonstrate your expertise and passion for the field.
✨Tip Number 3
Prepare to discuss specific projects where you've driven customer insights or personalization initiatives. Concrete examples will help illustrate your impact and strategic thinking.
✨Tip Number 4
Network with professionals in the fashion retail industry. Engaging with others in similar roles can provide valuable insights and potentially lead to referrals that could strengthen your application.
We think you need these skills to ace Head of Analytics & Data Science
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your strong background in Customer Analytics and any previous experience managing Data Science teams. Use specific examples that showcase your leadership skills and successful projects.
Showcase Technical Skills: Detail your technical expertise in analytics tools and methodologies. Mention any relevant programming languages, statistical techniques, or data visualization tools you are proficient in, as these are crucial for the role.
Tailor Your Application: Customize your CV and cover letter to align with the job description. Address how your experience relates to the responsibilities mentioned, such as promotional sales initiatives and funnel pipeline optimization.
Demonstrate Stakeholder Management: Include examples of how you have effectively managed stakeholders in previous roles. This could involve collaboration with other departments or presenting insights to senior management, which is key for this position.
How to prepare for a job interview at Workonblockchain
✨Showcase Your Customer Analytics Expertise
Be prepared to discuss specific projects where you've successfully utilized customer analytics. Highlight your understanding of customer behavior and how it can drive business decisions.
✨Demonstrate Leadership Skills
Since you'll be managing a matrix team, share examples of how you've effectively led teams in the past. Discuss your approach to mentoring and developing talent within your team.
✨Prepare for Technical Questions
Expect questions related to data science methodologies and tools. Brush up on your knowledge of statistical models, machine learning techniques, and any relevant software you’ve used.
✨Understand the Business Context
Research the company’s current market position and challenges. Be ready to discuss how your analytics strategies can contribute to promotional sales, stock replenishment, and overall business growth.
