Senior/Staff Data Analyst, Storefront

About Quince

Quince is a destination for builders, creators, innovators, and operators who want to come together and challenge the status quo. Our mission is simple: make really high quality essentials for really low prices, fairly and sustainably. We deliver on that mission through a unique manufacturer-to-consumer (M2C) model eliminating the layers of traditional retail that add cost.

What began with a small assortment of elevated basics has quickly grown into a cross-category brand spanning apparel, accessories, home goods, and more. Today, tens of millions of people across a growing number of countries come – and return – to Quince because they trust us to deliver.

Our Culture

Quince is a culture built for builders by builders. Our way of working starts with a blank sheet of paper. We question conventional thinking, use technology and data to uncover new opportunities, and move quickly to turn ideas into reality.

About the Role

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 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.

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
• 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
• Apply advanced statistical and analytical techniques to forecast trends, measure causal impact, and support strategic decision-making
• Partner with global analytics teams to improve data quality and governance

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
• 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; exposure to machine learning, causal analysis and predictive modeling.

Why Quince?

Joining Quince means being part of a mission-driven team reshaping retail. You will work alongside talented colleagues, tackle meaningful challenges, and contribute to building a more sustainable, accessible future for customers and partners alike.