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For Companies At a Glance
- Tasks: Lead a team of 12 in customer insights and data science initiatives.
- Company: Join a high-growth fashion retailer making waves in the industry.
- Benefits: Enjoy a competitive salary of £110,000-£120,000 and hybrid work options.
- Why this job: Be at the forefront of analytics and personalization in a dynamic retail environment.
- Qualifications: Strong experience in customer analytics and managing data science teams required.
- Other info: This role offers a unique opportunity to shape data-driven strategies.
The predicted salary is between 88000 - 120000 £ per year.
Head of Analytics & Data Science Liverpool (Hybrid – 3x Days a Week in Office) £110,000-£120,000 THE COMPANY A high-growth fashion retailer is seeking a Head of Analytics & Data Science to lead on all things customer insight & personalisation! THE ROLE As the Head of Analytics & Data Science, you’ll manage a matrix team of 12 across customer, loyalty & trading analytics as well as a team of Data Scientists. You will lead initiatives around promotional sales, stock replenishment, weather models and funnel pipeline optimization. You will have considerable experience working within both the customer analytics & data science space and be comfortable managing people as well as stakeholders. YOUR SKILLS AND EXPERIENCE Strong Customer Analytics experience Experience managing Data Science teams / functions THE BENEFITS £110,000-£120,000 Desired Skills and Experience Head of Data Science – Management – Analytics
Head of Data Science employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Science
✨Tip Number 1
Make sure to showcase your leadership skills in analytics and data science. Highlight any previous experience managing teams and how you’ve driven successful projects in customer insights and personalization.
✨Tip Number 2
Familiarize yourself with the latest trends in customer analytics and data science. Being able to discuss current methodologies and tools during your interview will demonstrate your expertise and passion for the field.
✨Tip Number 3
Prepare examples of how you've optimized processes or improved customer engagement through data-driven decisions. Real-world applications of your skills can set you apart from other candidates.
✨Tip Number 4
Network with professionals in the fashion retail industry. Engaging with others in the field can provide valuable insights and potentially lead to referrals that could help you land the job.
We think you need these skills to ace Head of Data Science
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly understand the responsibilities and expectations of the Head of Analytics & Data Science position. Highlight your experience in customer analytics and data science management in your application.
Tailor Your CV: Customize your CV to emphasize your relevant experience in managing data science teams and your expertise in customer analytics. Use specific examples that demonstrate your leadership skills and successful projects.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and analytics in the fashion retail industry. Discuss how your background aligns with the company's goals and how you can contribute to their growth.
Highlight Key Achievements: In both your CV and cover letter, make sure to highlight key achievements related to promotional sales, stock replenishment, and funnel optimization. Use metrics to quantify your impact where possible.
How to prepare for a job interview at Harnham
✨Showcase Your Leadership Experience
As a candidate for the Head of Analytics & Data Science, it's crucial to highlight your experience in managing teams. Be prepared to discuss specific examples of how you've led data science initiatives and managed cross-functional teams effectively.
✨Demonstrate Customer Analytics Expertise
Since the role focuses heavily on customer insights, make sure to prepare case studies or examples that showcase your strong background in customer analytics. Discuss how your insights have driven business decisions in previous roles.
✨Prepare for Technical Questions
Expect to face technical questions related to data science methodologies and analytics tools. Brush up on your knowledge of statistical models, machine learning techniques, and any relevant software you’ve used in past projects.
✨Engage with Stakeholder Management Scenarios
Given the importance of stakeholder management in this role, be ready to discuss how you've successfully communicated complex data insights to non-technical stakeholders. Prepare examples that illustrate your ability to bridge the gap between data science and business needs.
