At a Glance
- Tasks: Analyse customer data to drive insights and improve business decisions.
- Company: Join a feel-good fashion brand with over 55 years of making style accessible.
- Benefits: Enjoy 40% staff discount, virtual GP access, and extra leave on your birthday.
- Other info: Flexible working patterns and a commitment to inclusion and diversity.
- Why this job: Make a real impact by turning data into actionable recommendations for customers.
- Qualifications: 3+ years in statistical analysis and proficiency in SQL, Python or R.
The predicted salary is between 37000 - 45000 £ per year.
We’re the feel-good fashion brand making style accessible and fun for over 55 years, on our website, mobile app and over 300 stores in the UK. By living our values - we play to win, customer obsessed, we are one and it starts with me - we deliver That New Look Feeling for our customers and each other.
The Role:
- Utilise advanced analytical techniques to understand customer behaviour, identify opportunities across acquisition, retention, loyalty and customer value, and turn data into recommendations that improve business decision-making.
WHATS IN IT FOR YOU:
- 40% staff discount plus friends & family discounts throughout the year
- Access to our reward platform for external discount and offers
- Virtual GP access for you and your children – it allows you to speak to a doctor at a time and date that suits you
- All employees are covered by our life assurance policy from day one
- Unlock extra leave with our buy more holiday scheme.
- Celebrate YOU! Enjoy an extra paid day off on your birthday each year
- Enhanced maternity, paternity and adoption leave, and shared parental leave (eligible after 2 years’ service).
- Spread the cost of your commute with interest-free season ticket loans
- Do your bit for the environment and save money with our Cycle2Work scheme
- We're proud to partner with the Retail Trust and Fashion & Textile Children's Trust
What you’ll be doing:
- Data Mining: Use data mining techniques to combine multiple large customer, transaction, campaign and digital datasets into new data marts, analytical models and reusable insight assets.
- Descriptive Analytics: Interpret data and present findings to stakeholders in a clear and impactful manner to drive data-driven decision making. Deliver deep-dive customer insight and recommendations that explain customer performance and behavioural trends.
- Advanced Analytics: Apply statistical and analytical techniques such as segmentation, clustering, predictive modelling and campaign measurement. Working knowledge of data science techniques including random forest, k-means and linear regression.
- Optimisation: Collaborate with cross-functional teams to identify opportunities for optimisation. Support initiatives across customer acquisition, retention, loyalty, lifecycle and marketing performance.
- Collaborate: Support a given analytical principle and deliver an agreed analytics strategy. Create stakeholder‑ready dashboards, reporting and insight packs while ensuring outputs are accurate, documented and governed.
- Development: Stay updated on industry trends and best practices in customer analytics, loyalty, CRM, marketing measurement and analytical techniques.
- Analytical mindset: Customer-focused mindset with the ability to think critically, challenge assumptions and solve complex business problems through data.
- Attention to detail: Ensure accuracy, consistency and reliability of analytical findings, maintaining high standards of quality and governance.
- Commercial curiosity: Demonstrate a strong interest in customer behaviour and how it impacts sales, loyalty, retention, profitability and long-term customer value.
- Clear communicator: Translate complex analytical concepts and findings into clear, impactful recommendations for both technical and non‑technical stakeholders.
- Continuous learning: Proactively seek opportunities to expand analytical, technical and customer knowledge, staying up to date with emerging best practices.
- Strong Opinions Loosely Held: Be vocal and maintain your point of view while remaining open to new ideas, challenge and opposing perspectives.
Who you are:
- Proficiency in statistical analysis, customer analytics and data visualisation tools. Experience working with large customer, marketing, loyalty or digital datasets. (3+ years)
- Proven experience writing code in languages such as SQL, Python or R.
- Experience applying advanced analytical techniques including segmentation, regression analysis, clustering, predictive modelling and campaign measurement. Knowledge of data science and machine learning techniques such as random forest, k-means and linear regression.
- Strong communication, presentation and data storytelling skills, with the ability to translate complex analytical findings into clear and commercially relevant recommendations.
- Good understanding of customer profiling, customer value, customer lifecycle measurement and behavioural analytics.
- Experience creating stakeholder‑ready dashboards, reporting solutions and insight packs using data visualisation tools.
- Knowledge of data quality, governance, documentation standards and ethical use of customer data.
- Insight quality and impact. Timely delivery. Stakeholder satisfaction. Adoption of customer insights and outputs. Development of analytical capability.
Why New Look?
We care about you and the planet and believe fashion should be a force for positive change. We celebrate inclusion and diversity in everything we do. We’re proud of our inclusive culture and our talented team members who embrace our shared purpose, behaviours and values.
We prioritise development, offering training to support your progression, so you can be your absolute best and achieve your goals.
We pride ourselves on being a flexible employer, our colleagues work a range of patterns. If you have a specific pattern in mind, we're keen to discuss this with you in line with the output needed for the role.
Senior Analyst – Customer Health employer: New Look
NEW LOOK is an excellent employer that fosters a collaborative and innovative work culture, particularly for those in the Senior Technologist role. With a strong emphasis on professional development and continuous improvement, employees are encouraged to grow their skills while contributing to high-quality product standards. Located in a vibrant retail environment, the company offers unique opportunities to influence product quality and drive meaningful change within the fashion industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Analyst – Customer Health
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like New Look!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Analyst – Customer Health at New Look.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like New Look.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Analyst – Customer Health at New Look, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Analyst – Customer Health
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at New Look, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at New Look. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at New Look
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at New Look!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.