At a Glance
- Tasks: Analyse data to drive insights and optimise the digital customer journey.
- Company: Join Ralph Lauren, a global leader in premium lifestyle products.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
- Why this job: Make an impact by turning data into actionable insights for a renowned brand.
- Qualifications: Strong analytical skills and experience in retail analytics required.
The predicted salary is between 35000 - 43000 £ per year.
Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren's reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets.
At Ralph Lauren, we unite and inspire the communities within our company as well as those in which we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion, and fairness for all.
Key Responsibilities:
- Ensure delivery of insights, reporting, and advanced analytics to drive business decisions and support optimising the digital customer journey, customer services, and performance marketing.
- Solve complex business problems/challenges through data analytics and communicate actionable insights to key stakeholders.
- Build key relationships with internal and external stakeholders, becoming a subject matter expert for one of the Digital teams.
- Develop a reporting suite that demonstrates ROI and profitability from various perspectives using Adobe and Microstrategy tools.
- Create and maintain reports and dashboards using web analytics data and data visualisation tools, aiming to automate reporting across the business.
- Monitor core KPIs vs. targets and proactively seek to solve complex business problems through data analytics.
- Play a key role in the experimentation process and UX improvements through A/B & MVT tests.
- Monitor competitors’ activities and provide updates on best cases and market trends.
- Liaise with appointed external agencies supporting digital analytics.
- Perform QA testing on web analytics tracking implementations to ensure data accuracy and integrity.
- Partner with developers and product teams to identify and resolve tracking issues before release.
- Create and maintain QA testing checklists and documentation to standardise validation processes.
- Support A/B test setup with pre- and post-launch QA to verify correct experiment configuration and data collection.
Qualifications:
- A strong quantitative university degree or equivalent (e.g. statistics, mathematics, physics, engineering).
- Strong experience in retail analytics, with the ability to turn data into actionable insights and communicate recommendations effectively.
- Experience of actively using data visualisation tools and enterprise Business Intelligence tools.
- Outstanding analytical skills and attention to detail.
- Excellent communication skills, both written and spoken.
- Experience of building scalable reporting and analytics.
- Experience of using relational databases and data mining tools.
Data Analyst, Digital Commerce, EMEA & LATAM employer: FashionUnited Group
FashionUnited Group is an excellent employer that values its employees by fostering a dynamic and supportive work culture in the heart of Manchester. With competitive salaries, performance-based bonuses, and a generous uniform allowance, we prioritise employee satisfaction and growth, offering ample opportunities for career advancement within the luxury retail sector. Join us to be part of a team that is dedicated to delivering exceptional service while enjoying the vibrant atmosphere of one of the UK's most exciting cities.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst, Digital Commerce, EMEA & LATAM
✨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 FashionUnited Group!
✨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 Data Analyst, Digital Commerce, EMEA & LATAM at FashionUnited Group.
✨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 FashionUnited Group.
✨Apply Directly through Our Website
When you find a suitable opening like Data Analyst, Digital Commerce, EMEA & LATAM at FashionUnited Group, 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 Data Analyst, Digital Commerce, EMEA & LATAM
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 FashionUnited Group, 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 FashionUnited Group. 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 FashionUnited Group
✨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 FashionUnited Group!
✨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.
