At a Glance
- Tasks: Dive into data and shape shipping strategy while collaborating with diverse teams.
- Company: Join Depop, a vibrant peer-to-peer fashion marketplace on a mission to make fashion circular.
- Benefits: Enjoy flexible working, generous leave, health benefits, and a supportive work environment.
- Other info: Be part of a diverse team that values innovation and personal growth.
- Why this job: Make a real impact in the fashion industry while developing your data science skills.
- Qualifications: Strong SQL skills, strategic thinking, and experience with A/B testing and visualisation tools.
The predicted salary is between 63000 - 77000 £ per year.
Depop is a peer-to-peer circular fashion marketplace where anyone can buy, sell and discover secondhand fashion. Our mission is simple: to make fashion circular by making secondhand as exciting and rewarding as buying new.
Founded in 2011, Depop’s diverse community has helped move resale into the mainstream, where buying secondhand is no longer an alternative, but how people of different ages now engage with fashion. Today, more than 56 million registered users come to Depop to find great value, express their own personal style and give clothes a longer life.
We aim 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 looking for a Product Data Scientist to join our Insights team to support our Shipping Team. You’ll partner closely with product, operations, engineering, and machine learning to deliver insights, drive experimentation, and shape how every item moves from seller to buyer.
This role sits at the intersection of technical depth and strategic impact. You’ll dive into data, pipelines and experimentation frameworks whilst helping shape shipping strategy, product direction and commercial outcomes.
What You’ll Do
- Influence product and business strategy: Shipping is full of big, open-ended problems. You’ll pin down the right question, then work with the team to shape an answer they can act on. You’ll help to inform our shipping strategy by connecting your analyses to broader company goals, helping the product team understand trade-offs, challenging assumptions and driving evidence based decision making.
- Own analytics for Shipping: Be the go-to data scientist for the Shipping team - deeply understanding buyer and seller behaviour, carrier and label economics, and the end-to-end delivery experience, measuring performance and finding opportunities to improve outcomes.
- Design and help evaluate experiments: Define hypotheses, monitor A/B tests, and conduct post experiment analyses. Provide clear recommendations on rollouts or iterations.
- Enable self-serve data driven decision making: Collaborate with product, platform and data teams to ensure scalable, accurate datasets. Build dashboards and reporting that drive awareness and actionable insights.
What We’re Looking For
- Strong SQL skills and experience querying large, complex datasets.
- Strategic thinker, comfortable structuring a nebulous problem statement and working it through to a clear recommendation.
- Working knowledge 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 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 in shipping, logistics or marketplace unit economics.
- Experience working with machine learning teams or embedding data science in ML-powered product features.
Additional Information
- Health + Mental Wellbeing: PMI and cash plan healthcare access with Bupa, subsidised counselling and coaching with Self Space, Cycle to Work scheme, Employee Assistance Programme (EAP) for 24/7 confidential support.
- Work/Life Balance: 25 days of annual leave with the option to carry over up to 5 days, up to 2 days of additional paid leave per year for volunteering, fully paid 4-week sabbatical after completion of 5 years of consecutive service.
- Flexible Working: MyMode hybrid-working model with Flex, Office-Based, and Remote options.
- Family Life: 20 weeks of paid parental leave for birth parents, 12 weeks for non-birth parents, IVF leave, shared parental leave, and paid emergency parent/carer leave.
- Learn + Grow: Twice-yearly development chats and yearly performance reviews, learning budget, upskilling our employees with company-wide training workshops.
- Your Future: Life Insurance (financial compensation of 3x your salary), pension matching up to 6% of full base salary with Aviva.
- Depop Extras: In-office Depop Shop and a packing station with free delivery.
Product Data Scientist in London employer: Depop
DEPOP is an excellent employer that fosters a collaborative and innovative work culture, where Senior iOS Engineers can thrive while leading architecture for impactful user experiences. Located in Greater London, employees enjoy flexible working options, comprehensive healthcare access, and generous leave policies, all of which support a healthy work-life balance. With opportunities for mentorship and professional growth, DEPOP is dedicated to empowering its team members to make meaningful contributions to the secondhand fashion marketplace.
StudySmarter Expert Advice🤫
We think this is how you could land Product Data Scientist in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Product Data Scientist 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!
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Craft a Tailored Cover Letter:For a full-time role at Depop, 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 Depop. 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 Depop
✨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 Depop!
✨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.
