Data Scientist (Product Analytics)

Data Scientist (Product Analytics)

Team: Insights

Location: Depop - London

Company Description

Depop is the community-powered circular fashion marketplace where anyone can buy, sell and discover desirable secondhand fashion. With a community of over 35 million users, Depop is on a mission to make fashion circular, redefining fashion consumption. Founded in 2011, the company is headquartered in London, with offices in New York and Manchester, and in 2021 became a wholly-owned subsidiary of Etsy. Find out more at www.depop.com Our mission is to make fashion circular and to create an inclusive environment where everyone is welcome, no matter who they are or where they’re from. Just as our platform connects people globally, we believe our workplace should reflect the diversity of the communities we serve. We thrive on the power of different perspectives and experiences, knowing they drive innovation and bring us closer to our users. We’re proud to be an equal opportunity employer, providing employment opportunities without regard to age, ethnicity, religion or belief, gender identity, sex, sexual orientation, disability, pregnancy or maternity, marriage and civil partnership, or any other protected status. We’re continuously evolving our recruitment processes to ensure fairness and are open to accommodating any needs you might have. If, due to a disability, you need adjustments to complete the application, please let us know by sending an email with your name, the role to which you would like to apply, and the type of support you need to complete the application to . For any other non-disability related questions, please reach out to our Talent Partners.

Life is about creating. That's why we're home to over 30 million artists, stylists, designers, sneakerheads — and you? We're the community-powered, circular-minded marketplace changing the world of online fashion. Now it's time to get inspired at Depop.

Responsibilities

Job description

We’re looking for a Product Data Scientist to join our Insights team. You’ll partner closely with product, engineering, and machine learning to deliver insights, drive experimentation, and shape the future of Depop’s product ecosystem.

This role sits at the intersection of technical excellence and strategic impact. You will not only dive deep into data, pipelines, and experimentation frameworks, but also influence product direction, user experience, and commercial outcomes.

What You’ll Do:

Provide analytics for a core product area 

Work as the go-to data scientist for a product domain. Deeply understand user behaviour, measure performance and find opportunities to improve outcomes.

Influence product and business strategy

Connect your analyses to broader company goals. Help the product team understand trade-offs, challenge assumptions and drive evidence based decision making. 

Design and help evaluate experiments

Define hypotheses, monitor A/B tests, and at times conduct post experiment analyses. Provide clear recommendations on rollouts or iterations.

Work together with other teams to enable self-serve data driven decision making

Collaborate with product, platform and data teams to ensure scalable, accurate datasets for analysis. Develop dashboards and reporting that drive awareness and actionable insights.

What We’re Looking For:

Strong SQL skills and experience querying large, complex datasets

Basic understanding of Python

Familiarity with ETL workflows and debugging data issues

Proven experience with A/B testing design and interpretation

Hands-on experience with visualisation tools (Looker, Tableau, or similar)

Excellent communication skills—able to explain complex topics clearly and persuasively

Commercial mindset with the ability to balance user and business needs

Strong sense of ownership, highly organised, and proactive

Comfortable working across ambiguity and fast-changing environments

Bonus Points

Experience in C2C marketplaces or mobile-first consumer products

Experience working alongside machine learning teams or embedding data science in ML-powered product discovery