At a Glance
- Tasks: Drive impact through analytics and support customer insights for Nectar partnerships.
- Company: Join a dynamic team at the London Store Support Centre.
- Benefits: Enjoy discounts, bonuses, flexible holidays, and health plans.
- Other info: Great opportunity for growth in a supportive environment.
- Why this job: Make a real difference in customer understanding and marketing strategies.
- Qualifications: Analytical mindset, basic coding skills, and strong communication abilities.
The predicted salary is between 30000 - 40000 £ per year.
We are seeking a highly motivated Associate Analyst to join our Customer & Loyalty Analytics team. The ideal candidate will be responsible for driving impact through analytics, deriving insightful findings, and contributing to potential recommendations. This role requires a foundational understanding of coding languages, data visualisation, and analytical methodologies. This role sits within the Nectar Partnerships Analytics team which focuses on delivering customer and marketing analytics and reporting for our Nectar coalition partnerships. You’ll help our partners understand their customers, their interactions with Nectar, and the purchases they make.
Responsibilities
- Drive impact through analytics by deriving insightful findings and contributing to recommendations.
- Support the Nectar Partnerships Analytics team in delivering customer and marketing analytics and reporting.
- Help partners understand customer behaviour, interactions with Nectar, and purchases.
- Apply foundational coding skills and data visualisation techniques to analyse datasets and present findings.
Qualifications and Skills
What we are looking for:
- Analytical Thinking: Identify relevant metrics, analyse trends, and provide contextual insights to support business decisions.
- Data Visualisation & Communication: Present findings using appropriate visualisations and confidently explain insights to stakeholders.
- Project Ownership & Prioritisation: Manage analytical requests independently, assess scope, and balance ad-hoc demands with existing commitments.
- Technical Proficiency: Foundational coding skills, understanding of relational databases, and ability to perform quality checks on standardised code.
- Methodological Knowledge: Experience or ability to explain common analytical methodologies accurately.
- Operational Awareness & Governance: Recognise data limitations, investigate anomalies, and adhere to data protection and security policies.
What we would like you to have:
- An innovative mind and a passion for solving problems.
- A university degree (2:1 or higher) with a numerate background is preferable but not mandatory.
- Basic knowledge of coding (ideally SQL); interest in Python and other tools.
- Knowledge of BI tools (e.g. Tableau) would be advantageous.
- Previous analytical experience showing application of insight to address business questions.
- Strong communication skills, a confident curiosity to explore analytical problems, with evidence of sharing insights to achieve actionable results.
Essential criteria:
- Experience or exposure to SQL with knowledge of functions, code structure and logic.
- Strong analytical thinking: ability to define analytical approaches, work with stakeholders, and deliver robust analysis.
- Clear communication: ability to translate complex methodology or results clearly to non-technical audiences.
Benefits
We offer a range of benefits. Examples include colleague discounts, pension scheme and life cover, potential performance-related bonuses, annual holiday allowance, optional additional holiday, season ticket loans, cycle to work scheme, health cash plans, pay advances, employee assistance programme, and maternity/paternity leave. Details vary by role and length of service. For full details, please visit the official careers site.
Associate Analyst in London employer: Retail
As a Home Delivery Driver with Retail, you will be part of a dynamic team that values flexibility and customer satisfaction. Our supportive work culture encourages personal growth through comprehensive training and varied hours, allowing you to balance your professional and personal life effectively. Join us in delivering not just groceries, but also exceptional service across the United Kingdom, while enjoying the unique advantage of working in a role that directly impacts our customers' daily lives.
StudySmarter Expert Advice🤫
We think this is how you could land Associate Analyst in London
✨Embrace Online Competitions
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We think you need these skills to ace Associate Analyst in London
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Retail, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Retail aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at Retail
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
