At a Glance
- Tasks: Uncover customer behaviour insights and drive growth for international storefronts using data science.
- Company: Join a fast-scaling tech company focused on innovation and collaboration.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional development.
- Other info: Work in a dynamic, transparent culture that values speed and accountability.
- Why this job: Make a real impact by shaping the future of e-commerce with data-driven decisions.
- Qualifications: 7+ years in analytics, strong SQL and Python skills, and a passion for problem-solving.
The predicted salary is between 60000 - 80000 € per year.
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. 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. 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.
Responsibilities
- 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.
Qualifications
- Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Data Science, or a related discipline. Advanced degree preferred.
- 7+ years of experience in product analytics, growth analytics, or data science roles within e‑commerce or technology environments.
- Strong expertise in SQL and experience working with large‑scale behavioral and transactional datasets.
- 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.
- Strong understanding of KPI development, growth frameworks, funnel analysis, and customer behavior analytics.
- Experience building dashboards and analytical tools using platforms such as Tableau, Looker, Mixpanel, or Streamlit.
- 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.
- Demonstrated ability to influence product direction and prioritization through data‑driven insights.
- Proven track record of independently managing multiple high‑impact initiatives in ambiguous environments.
- Based in Berlin or London with the ability to work from the office 4 days per week.
Preferred Qualifications
- 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.
Equal Opportunity & Hiring Integrity
Quince provides equal employment opportunities to all employees and applications for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran or military status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Quince is committed to providing reasonable accommodations to qualified individuals with disabilities. If you need a reasonable accommodation to complete your application or to perform the essential functions of a role at Quince, please let us know by completing this accommodation form. We review all requests individually and will work with you to determine appropriate accommodations on a case‑by‑case basis. Employment is contingent upon successful completion of a background check. Quince will conduct background checks in compliance with applicable federal, state, and local laws.
Staff Data Analyst, Storefront employer: Quince
Quince is an exceptional employer that fosters a dynamic and collaborative work culture, particularly for the Staff Data Analyst role based in Berlin or London. With a strong emphasis on transparency, accountability, and high standards, employees are encouraged to take ownership of their projects while benefiting from ample opportunities for professional growth and development. The company’s commitment to data-driven decision-making and support for international expansion makes it an exciting place for those looking to make a meaningful impact in a fast-paced environment.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Analyst, Storefront
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or a personal project that highlights your analytical prowess. This is your chance to demonstrate how you can turn data into actionable insights.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to data analysis. Think about how you’d tackle real-world problems and be ready to share your thought process.
✨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, we love seeing candidates who are proactive!
We think you need these skills to ace Staff Data Analyst, Storefront
Some tips for your application 🫡
Show Your Analytical Skills:When writing your application, make sure to highlight your analytical prowess. Use specific examples from your past experiences that demonstrate how you've used data to drive decisions and uncover insights. We want to see your curiosity and problem-solving skills shine through!
Tailor Your Application:Don’t just send a generic application! Tailor your CV and cover letter to reflect the key responsibilities and qualifications mentioned in the job description. Show us how your background aligns with our needs for the Staff Data Analyst role, especially in e-commerce and analytics.
Be Clear and Concise:We appreciate clarity! Make sure your application is easy to read and straight to the point. Avoid jargon unless it’s relevant, and focus on communicating your achievements and skills in a way that’s accessible to both technical and non-technical audiences.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining our team at StudySmarter!
How to prepare for a job interview at Quince
✨Know Your Data Inside Out
Make sure you’re well-versed in the data analytics tools and techniques mentioned in the job description. Brush up on your SQL and Python skills, and be ready to discuss how you've used these in past roles to drive business decisions.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex analytical challenges in ambiguous environments. Think about specific instances where your insights led to measurable improvements in customer experience or business performance.
✨Understand the Business Context
Familiarise yourself with the company’s international storefronts and their growth strategies. Be prepared to discuss how your analytical skills can directly contribute to their goals, especially in emerging markets.
✨Communicate Clearly and Confidently
Practice explaining complex analyses in simple terms. You’ll need to convey your findings to both technical and non-technical stakeholders, so focus on clarity and impact in your communication style.
