At a Glance
- Tasks: Drive growth in emerging storefront markets through data analysis and strategic recommendations.
- Company: Join a dynamic e-commerce company focused on international expansion and innovation.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional development.
- Other info: Work in a fast-paced, collaborative culture that values transparency and accountability.
- Why this job: Make a real impact by shaping customer experiences and driving business success with data.
- Qualifications: 7+ years in analytics, strong skills in SQL, Python, and A/B testing.
The predicted salary is between 54000 - 66000 £ per year.
This role will be jointly accountable for helping drive the growth and success of emerging storefront markets by identifying the highest-impact opportunities across product experience, customer behavior, and operational performance.
Partner closely with product, engineering, merchandising, and business stakeholders to support the launch and growth of new international storefronts and customer experiences.
Develop scalable dashboards, KPI frameworks, and automated reporting to monitor business health across acquisition, engagement, conversion, retention, orders, and revenue.
Identify and quantify the key drivers behind storefront performance and customer behavior, translating findings into actionable recommendations for product and business teams.
Lead deep-dive analyses to uncover growth opportunities, diagnose friction points, and improve the end-to-end customer journey.
Design, analyze, and interpret A/B tests and other experimentation frameworks to measure product impact and guide roadmap prioritization.
Apply advanced statistical and analytical techniques to forecast trends, measure causal impact, and support strategic decision-making in new and growing markets.
Partner with global analytics teams to improve data quality, governance, instrumentation, and best practices in analytics and AI-enabled workflows.
Help define success metrics and analytical frameworks for new product initiatives and international expansion efforts.
Act as a strategic thought partner to cross-functional teams by proactively surfacing insights, risks, and opportunities that drive measurable business outcomes.
Contribute to building a high-performing analytics culture grounded in rigor, speed, curiosity, and ownership.
The ideal candidate is deeply analytical, highly curious, and motivated by using data science to shape the trajectory of fast-scaling international storefronts. They are skilled at uncovering the underlying drivers of customer behavior, business performance, and product outcomes, and translating those insights into clear opportunities for growth.
They thrive in ambiguous, fast-moving environments where they are expected to move beyond reporting into proactive problem solving, experimentation, and strategic influence. This person is energized by building from zero-to-one, partnering closely with product, engineering, merchandising, and business teams to help new storefronts scale successfully.
The ideal candidate combines strong technical depth in analytics and experimentation with strong business judgment. They are comfortable owning complex analytical initiatives end-to-end, influencing prioritization through data, and helping teams focus on the highest-leverage opportunities to improve customer experience and accelerate growth in emerging markets.
Strong understanding of KPI development, growth frameworks, funnel analysis, and customer behavior analytics.
Lastly, they are excited by a culture where transparency, speed, accountability, and high standards are core operating principles, and where data is central to decision-making across the organization.
Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Data Science, or a related discipline. Advanced degree preferred.
Experience building dashboards and analytical tools using platforms such as Tableau, Looker, Mixpanel, or Streamlit.
Based in Berlin or London with the ability to work from the office 4 days per week.
Advanced proficiency in Python for analytics, experimentation, statistical modeling, and data exploration.
Extensive experience designing and evaluating experiments, including A/B testing methodologies and causal inference approaches.
Demonstrated ability to influence product direction and prioritization through data-driven insights.
7+ years of experience in product analytics, growth analytics, or data science roles within e-commerce or technology environments.
Proven track record of independently managing multiple high-impact initiatives in ambiguous environments.
Strong expertise in SQL and experience working with large-scale behavioral and transactional datasets.
Ability to move fluidly between strategic thinking and hands-on execution in a fast-paced environment.
Strong communication skills with the ability to synthesize complex analyses into clear business recommendations for technical and non-technical audiences.
Experience supporting international expansion, marketplace growth, or multi-region e-commerce businesses.
Experience analyzing customer journeys across storefront, acquisition, merchandising, and checkout experiences.
Exposure to machine learning, causal analysis and predictive modeling applications in consumer or growth analytics.
Experience working in high-growth, highly cross-functional product organizations.
Staff Data Analyst (Storefront) in London employer: Quince
Quince is an exceptional employer that fosters a vibrant and collaborative work culture, particularly for the Brand Designer role based in dynamic cities like London, Madrid, or Berlin. With a strong emphasis on employee growth, Quince offers opportunities to refine your design skills while working on impactful campaigns across various digital channels. The company values creativity and innovation, ensuring that every team member contributes to a cohesive brand aesthetic while enjoying a supportive environment that prioritises work-life balance and inclusivity.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Analyst (Storefront) in London
✨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 Quince!
✨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 Staff Data Analyst (Storefront) at Quince.
✨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 Quince.
✨Apply Directly through Our Website
When you find a suitable opening like Staff Data Analyst (Storefront) at Quince, 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 Staff Data Analyst (Storefront) 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 Quince, 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 Quince. 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 Quince
✨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 Quince!
✨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.
