At a Glance
- Tasks: Drive market insights and operational learning to enhance decision-making and continuous improvement.
- Company: Dynamic e-commerce leader with a focus on innovation and collaboration.
- Benefits: Flexible hybrid working, competitive salary, and a supportive environment for growth.
- Other info: Join a diverse team committed to inclusivity and creativity.
- Why this job: Make a real impact by shaping marketplace strategies and driving improvements across teams.
- Qualifications: Experience in analytics, strategy, or e-commerce; strong data interpretation skills.
The predicted salary is between 60000 - 80000 £ per year.
We’re looking for a data‑driven professional who can bring together market insight and operational learning to help teams make informed decisions and continuously improve.
This role can be based from London, France, Poland or Spain, with frequent travel between sites.
Responsibilities
- Define and own the Group Marketplace market intelligence agenda.
- Gather and analyse marketplace performance data, seller trends and market developments to identify opportunities for improvement.
- Monitor competitor activity, emerging marketplace models and changes across the wider e‑commerce landscape.
- Identify, document and share best practices through clear frameworks and a centralised knowledge base, helping teams avoid duplication and apply operational learnings consistently across banners.
- Lead the roll‑out and adoption of best practices across banners, partnering with local teams to embed consistent standards and ways of working while tracking impact to drive continuous improvement.
- Translate complex data into clear narratives for senior stakeholders, supporting business cases, prioritisation, OKRs and investment decisions in close collaboration with Marketplace, Product, Finance and Operations teams.
- Drive structured post‑launch reviews and embed a test‑and‑learn culture, ensuring operational insights are captured, reused and scaled across banners to support continuous improvement.
Qualifications
- Experience in strategy, analytics, market intelligence, consulting or e‑commerce/marketplace environments.
- Strong exposure to cross‑functional environments (e. g. working with Product, Operations, Finance or Commercial teams).
- Experience in building or scaling knowledge‑management frameworks, best‑practice sharing or continuous‑improvement initiatives.
- Demonstrated ability to translate complex data into clear recommendations for senior stakeholders.
- Familiarity with data visualisation and analytics tools (e. g. Excel, SQL, Tableau, Power BI or similar).
- Experience leveraging automation, data tooling or AI (e. g. analytics automation, insight generation, knowledge capture) to improve efficiency and scalability.
- How We Work
We believe in flexibility and balance.
Our hybrid model blends home working for focus with time spent connecting and collaborating – whether in our offices or at offsite locations.
On average, around 60% of your time will involve in‑person collaboration.
What We Offer
An inclusive environment where your potential is limited only by your imagination.
We encourage new ideas, support experimentation, and strive to create a workplace where everyone can be their best self.
We also offer a competitive benefits package and plenty of opportunities to stretch and grow your career.
Diversity & Inclusion
Our customers come from all walks of life – and so do we.
We’re committed to ensuring all colleagues, future colleagues and applicants are treated equally, regardless of age, gender, marital or civil partnership status, ethnicity, culture, religion, belief, political opinion, disability, gender identity, gender expression or sexual orientation.
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StudySmarter Expert Advice🤫
We think this is how you could land Marketplace Market Intelligence & Operational Learning Senior Manager in London
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We think you need these skills to ace Marketplace Market Intelligence & Operational Learning Senior Manager in London
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 hackajob, 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 hackajob. 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 hackajob
✨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!
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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
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✨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.
