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 experience.
- Benefits: Enjoy a 40% staff discount, virtual GP access, and extra leave on your birthday.
- Other info: Flexible working patterns and a commitment to inclusion and development.
- Why this job: Make a real impact by transforming data into actionable recommendations.
- Qualifications: 3+ years in customer analytics with skills in SQL, Python or R.
The predicted salary is between 37800 - 46200 £ 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: (2-3 Days In Office) 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
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 1 Year FTC) in London 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 1 Year FTC) in London
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like New Look before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like New Look.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like New Look.
We think you need these skills to ace Senior Analyst - Customer Health 1 Year FTC) in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at New Look, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to New Look, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab New Look’s attention and show the tangible impact of your work.
How to prepare for a job interview at New Look
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at New Look.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at New Look.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at New Look.