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- Tasks: Transform complex data into actionable insights that drive business decisions.
- Company: Join Mous, a leading tech brand focused on performance and innovation.
- Benefits: Enjoy competitive salary, growth opportunities, and a fun hybrid work environment.
- Other info: Collaborative team with regular socials and a commitment to diversity.
- Why this job: Make a real impact in a fast-paced, data-driven culture while developing your skills.
- Qualifications: 0-2 years in data roles; strong analytical and communication skills required.
The predicted salary is between 30000 - 40000 £ per year.
About Mous
We are Mous. (Pronounced mouse, not moose.) People deserve tech and lifestyle products that are fit for purpose, perform as promised, and empower them to be their best. That’s why we’re building the go-to brand for products that genuinely deliver. For over 10 years, we’ve pushed product performance to its limits, designing from first principles, validating through real-world testing, and investing millions in R&D. In parallel, we’ve built world-class in-house marketing capabilities, creating highly engaging, performance-led content that proves what our products can do and resonates with a passionate, fast-growing community around the brand. From throwing phones off dams to launching category-defining products, our ambition is simple: raise the standard of the industry and build one of the most effective consumer brands in the world.
About the Role
We’re looking for a highly analytical and commercially-minded Data Analyst to join our fast-growing team here in the UK. This is a high-impact role sitting at the intersection of data, strategy, and business performance, with the opportunity to accelerate your growth by owning key projects and taking on increasing responsibility as you drive measurable results. You’ll be at the forefront of turning complex datasets into clear, actionable insights that directly influence decision-making across the company. You’ll work closely with cross-functional teams (Growth, Product, Marketing, and Leadership), to champion the use of data across the business to identify what’s working, what isn’t, and where the biggest opportunities lie. This role is designed for someone who wants ownership early, thrives in a fast-paced environment, and is excited to see the tangible impact of their work on business performance. If you would like to join a collaborative, data-driven team that values knowledge sharing, continuous improvement, and professional development, this role is for you!
About You
As a Data Analyst at Mous, you’ll possess a unique blend of commercial prowess, problem-solving skills, and a passion for data-driven decision making. You are not only detail-oriented but also capable of seeing the bigger picture, transforming complex data sets into actionable insights. Your adaptability and desire to continuously learn make you an ideal candidate for navigating the dynamic landscape of eCommerce. A collaborative team player, you excel at communicating complex data findings in a clear, concise manner, making data accessible to all levels of the company. You will be pivotal in understanding and addressing the data needs of various departments, including Ecommerce, Pricing, and Growth. Your role will be multifaceted, from conducting thorough analyses and developing insightful dashboards to driving operational efficiencies and leading projects. You will be at the forefront of promoting a data-driven culture, empowering the organisation through informed decision-making and self-sufficient data management.
Key Responsibilities:
- Conduct comprehensive data analysis to support business decision-making, identifying trends, patterns, and insights.
- Build and refine dynamic dashboards to monitor key performance indicators (KPIs) and objectives and key results (OKRs), enabling access to cross-departmental data.
- Proactively identify areas for improvement within the company's processes and systems and implement automated solutions.
- Lead and support strategic cross-department initiatives to drive value. E.g. Pricing Optimisation, Segmentation Analysis, Marketing Mix Modelling.
- Support in building out fundamental data sources, to allow analysis of data from multiple key platforms.
- Communicate insights and present key findings to relevant stakeholders while acting as a point of call for data-related questions.
How will success be measured?
- Delivering clear, actionable insights that directly influence business decision making.
- Developing a strong understanding of our data infrastructure at Mous.
- Building high-quality, durable dashboards and data models that improve access to cross-departmental data.
- Proactively identifying and resolving opportunities and inefficiencies.
- Collaborating effectively across teams, acting as a trusted point of contact and champion of best data practices.
Skills requirements:
- Hard skills: 0-2 years of experience in a data-related role, or relevant higher education/qualifications. A demonstrable commercial understanding with the ability to value and prioritise work ruthlessly. A knack for numbers with the confidence to tackle and interpret large, complex data sets. Experience in SQL, Excel and a dashboarding tool (PowerBI preferred).
- Soft skills: Strong problem solver – never afraid to get stuck into the detail to uncover insights. Strong communication skills, with the ability to translate insights clearly for technical, non-technical, and senior stakeholders, while effectively managing both internal teams and external partners.
- Nice to have: Experience with DBT for analytics engineering. Data modelling skills to structure and optimise datasets. Proficiency in Python for data analysis and automation. Familiarity with R for statistical analysis and reporting. Experience working within a D2C or consultancy environment.
Our Offer
We operate a hybrid working model, typically spending at least three days a week in our Hoxton office to maintain our collaborative and high-energy culture. Benefits include:
- Significant opportunity for growth, ownership, and career progression.
- Competitive salary reflective of experience and impact.
- 30% Friends & Family discount on all Mous products.
- 25 days’ holiday + 8 bank holidays.
- 1 month paid leave after 5 years’ service.
- Cycle to Work Scheme.
- Charlie HR perks and discounts.
- Regular socials, events, and on-site activities (including an on-site gym).
Our Values
Get Results – We take accountability, prioritise impact, and push standards higher. Work Together – We collaborate openly, challenge constructively, and learn from each other. Enjoy the Ride – We stay agile, embrace change, and enjoy building something special together.
About Our Commitment
Mous is an equal opportunity employer. We celebrate individuality and are committed to building a diverse team with a wide range of experiences, perspectives, and backgrounds.
Data Analyst: Turn Data Into Strategy & Growth employer: Mous Products Ltd.
Contact Detail:
Mous Products Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst: Turn Data Into Strategy & Growth
✨Tip Number 1
Network like a pro! Reach out to current employees at Mous on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Data Analyst role. Personal connections can give you an edge!
✨Tip Number 2
Prepare for the interview by diving deep into Mous's products and values. Understand how data drives their business decisions. This will not only impress your interviewers but also help you articulate how you can contribute to their goals.
✨Tip Number 3
Showcase your analytical skills during the interview. Bring examples of past projects where you turned complex data into actionable insights. This will demonstrate your ability to make a real impact at Mous right from the start.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the Mous team.
We think you need these skills to ace Data Analyst: Turn Data Into Strategy & Growth
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Data Analyst role. Highlight your analytical skills, experience with SQL and Excel, and any relevant projects that showcase your ability to turn data into actionable insights.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data and how you can contribute to our mission at Mous. Share specific examples of how you've used data to drive results in previous roles or projects.
Showcase Your Problem-Solving Skills: In your application, don’t just list your skills; demonstrate them! Include examples of how you've tackled complex data challenges and what impact your solutions had on the business.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us!
How to prepare for a job interview at Mous Products Ltd.
✨Know Your Data Inside Out
Before the interview, dive deep into your past data projects. Be ready to discuss specific datasets you've worked with, the tools you used (like SQL or PowerBI), and the insights you derived. This shows you're not just familiar with data but can also translate it into actionable strategies.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex problems using data analysis. Think about situations where you identified trends or inefficiencies and how your insights led to improvements. This will demonstrate your analytical mindset and ability to drive results.
✨Communicate Clearly and Confidently
Practice explaining your data findings in simple terms. You might be speaking to non-technical stakeholders, so being able to convey complex information clearly is key. Use examples from your experience to illustrate how you’ve made data accessible to all levels of a business.
✨Emphasise Collaboration and Adaptability
Mous values teamwork and adaptability, so be prepared to discuss how you've worked with cross-functional teams in the past. Share instances where you’ve collaborated on projects, highlighting your role in promoting a data-driven culture and how you adapt to changing environments.