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 [email protected]. For any other non-disability related questions, please reach out to our Talent Partners.
We are looking for a Product Manager to lead our Trust Detection team. This is a high-stakes role sitting at the intersection of Machine Learning, Policy, and User Safety. You will lead a specialized team of ML scientists and backend engineers to build the "immune system" of our platform.
Your mission is to move beyond reactive moderation toward proactive defense. You will be responsible for the models that decide who is allowed to participate in our ecosystem and who is blocked from causing harm.
Technical Strategy & Roadmap: Partner with ML Scientists to shift from conversation-level detection to sophisticated user-level models. You will define the vision for identifying bad actors based on 40+ features across historical enforcement, user reports, and listing behavior.
Precision-Driven Execution: Own the trade-offs between catching "bad actors" and protecting legitimate sellers. You will aim for high-precision targets to ensure we catch high-volume counterfeiters and phishers before they impact our users.
System Evolution: Oversee the development of auto-retraining systems and models for a wide range of policy violations, from counterfeit goods, prohibited items, abusive behaviour, and any unsafe content for our community.
Resource & Stakeholder Management: Navigate a lean, high-output environment. You will be the bridge between Operations leadership and the technical team.
Must-haves:
Technical Foundation: You possess a strong foundational understanding of machine learning—whether gained through professional PM experience, engineering roles, or dedicated personal projects. We value fast learners who can grasp the mechanics of model training and feature engineering and are eager to apply that technical DNA to solve complex product challenges.
Analytical Rigor: You live and breathe with data. You can dive into performance metrics and understand why a model is flagging specific accounts or behaviors
User Outcome Focus: You can balance rigorous policing with a user-first mindset, ensuring our models accurately evaluate and protect genuine sellers while minimizing the friction of false positives.
Resilience & Speed: Trust & Safety could sometimes be a "cat-and-mouse" game. You are comfortable with fast-scaling environments and can pivot quickly when new fraud trends emerge.
Communication: Ability to explain complex ML logic to non-technical stakeholders while maintaining deep technical credibility with your Engineering partners.
Bonus points:
Technical Background: A background as Data Analyst, Engineer, or ML Scientist is a big plus!
Domain Expertise: Direct experience in Trust & Safety, Fraud, or Risk at a marketplace or social platform.
Marketplace Experience: Understanding the marketplace dynamics and the unique frictions in peer-to-peer interactions.
Community Mindset: A passion for Depop’s mission of circularity and self-expression. Especially if you’re already part of the Depop community.
Additional Information
Health + Mental Wellbeing
PMI and cash plan healthcare access with Bupa
Subsidised counselling and coaching with Self Space
Cycle to Work scheme with options from Evans or the Green Commute Initiative
Employee Assistance Programme (EAP) for 24/7 confidential support
Mental Health First Aiders across the business for support and signposting
Work/Life Balance:
25 days annual leave with option to carry over up to 5 days
1 company-wide day off per quarter
Impact hours: Up to 2 days additional paid leave per year for volunteering
Fully paid 4 week sabbatical after completion of 5 years of consecutive service with Depop, to give you a chance to recharge or do something you love.
Flexible Working: MyMode hybrid-working model with Flex, Office Based, and Remote options *role dependant
All offices are dog-friendly
Ability to work abroad for 4 weeks per year in UK tax treaty countries
Family Life:
18 weeks of paid parental leave for full-time regular employees
IVF leave, shared parental leave, and paid emergency parent/carer leave
Learn + Grow:
Budgets for conferences, learning subscriptions, and more
Mentorship and programmes to upskill employees
Your Future:
Depop Extras:
