Depop
Senior Machine Learning Scientist
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Company Description
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 believe that everything you want already exists, and our role is to help people discover it.
Powered by a team of over 500 people, our company is headquartered in London, with offices in New York. In 2021, Depop became a wholly-owned subsidiary of Etsy - the global marketplace for unique and creative goods - and continues to operate as a standalone company. For more information, visit www.depop.com.
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 continuously evolving our recruitment processes to ensure fairness and are open to accommodating any needs you might have.
AI Disclosure: We use AI tools (Google Gemini) to help our team source and review applications for roles with a high volume of applications. These tools assist our recruiters in identifying great talent but do not replace human decision-making. At Depop, every hiring decision is made by a human.
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 adjustments@depop.com.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Role
Depop is looking for a Senior Machine Learning Scientist to join our Pricing team in the UK. You will work alongside a cross-functional team of Product Managers, Engineers, Analysts and fellow Machine Learning Scientists, playing a key role in building the machine learning models that power Depop’s pricing recommendations and our shipping pricing and optimisation strategies.
As a senior member of the team, you will be expected to take ownership of high-impact projects, lead technical direction on core modelling efforts, and mentor others while working across multiple domains and stakeholders.
Responsibilities
- Research, design, and deliver robust machine learning solutions to tackle problems across the pricing and shipping space, spanning both prediction and decision-making under business constraints
- Lead efforts to productionise and scale these models, partnering with ML and backend engineers so they run reliably on our systems
- Identify and define requirements from multiple stakeholders across Pricing and Shipping, and lead the design of machine learning solutions to solve applied business problems
- Set up and conduct large-scale experiments to test hypotheses and guide model and product improvements, ensuring statistical rigour and real-world applicability
- Keep up to date with applied research, contribute to internal knowledge sharing and ML best practices, and apply new techniques for prediction, causal inference, and optimisation
- Participate in team ceremonies, such as technical whiteboarding sessions, planning, and roadmapping
- Communicate technical findings clearly and confidently to both technical and non-technical audiences
Qualifications
Skills and Experience
- Significant experience working as a Machine Learning Scientist, with a proven track record of delivering and scaling models that solve complex, real-world problems
- Deep understanding of machine learning concepts and experience applying them in production settings, using frameworks such as PyTorch, TensorFlow, or gradient boosting libraries
- Experience with causal inference, uplift modelling, or optimisation under constraints, and comfort reasoning about decisions rather than predictions alone
- Strong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles
- Ability to lead end-to-end ML projects, work independently in ambiguous problem spaces, and mentor junior team members
- Strong collaboration and communication skills, with experience aligning technical approaches with cross-functional teams and stakeholders
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Bonus Points
- Experience with pricing models, promotions or incentive allocation, or revenue optimisation
- Experience with experiment design and conducting A/B tests
- Experience with bandits, reinforcement learning, or other explore-exploit approaches
- Experience with Databricks and PySpark
- Experience working with AWS or another cloud platform (GCP/Azure)
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 of annual leave with the option to carry over up to 5 days
- Impact hours: 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 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-dependent
- All offices are dog-friendly
Family Life
- For birth parent: 20 weeks of paid parental leave for full-time regular employees
- For non-birth parents: 12 weeks of paid parental leave for full-time regular employees
- 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, materials and resources
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 (that’s free!) and a packing station with free delivery.
- Special milestones are celebrated with gifts and rewards!
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Location