At a Glance
- Tasks: Lead the design and deployment of advanced ranking models for Depop's app.
- Company: Join a dynamic team at Depop, a leading platform in personalised recommendations.
- Benefits: Enjoy flexible working, health benefits, and generous leave policies.
- Other info: Mentorship opportunities and a supportive work culture await you.
- Why this job: Make a real impact by innovating with cutting-edge machine learning techniques.
- Qualifications: Proven experience in machine learning and strong programming skills in Python.
The predicted salary is between 48000 - 84000 £ per year.
Depop is looking for a talented Staff ML Scientist to join our Ranking ML team in the UK. You will work alongside a cross-functional team of Product Managers, ML Engineers, and fellow ML Scientists, helping build and maintain ranking models to power Depop's app, serving millions of personalised results to users daily. As a staff-level member of the team, you will be expected to set the technical vision, lead high-impact initiatives, and mentor and coach others to drive innovation at scale, while working across multiple domains and stakeholders.
Responsibilities
- Lead the design and deployment of advanced ranking models for Depop's entire app, covering personalised recommendations, search results and other surfaces.
- Collaborate closely with cross-functional partners (product, engineering, data) to define problems, translate them into scalable solutions, and deliver measurable business outcomes.
- Lead the end-to-end lifecycle of ML projects: from ideation, data acquisition, feature engineering, training, and evaluation to deployment and ongoing iteration.
- Drive innovation in ranking by researching and integrating emerging ML techniques, frameworks, and tooling, while contributing technical expertise to long-term product and data strategy.
- Mentor, coach, and set technical direction within the Ranking ML team, helping others grow and innovate.
- Act as a thought leader in the ranking space, sharing learnings internally, engaging with the wider ML community, and showcasing our work externally.
Qualifications
- Significant experience working as a Machine Learning Scientist, with a proven track record of delivering and scaling models that solve complex, real-world problems with measurable business impact.
- Proven track record in designing and optimizing learning-to-rank models.
- Deep understanding of machine learning concepts and frameworks.
- Proven ability to productionize ML models and pipelines: from prototyping to deployment, with strong experience in monitoring, iteration, and troubleshooting.
- Advanced programming skills in Python and familiarity with ML frameworks such as PyTorch, TensorFlow, or similar.
- Experience leading projects and mentoring engineers or scientists, with a track record of fostering team growth and technical excellence.
- Excellent communication skills: able to bridge technical and non-technical stakeholders and influence decision making.
- Committed to responsible AI practices, including attention to ethics, fairness, and inclusivity.
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.
- 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: Life Insurance (financial compensation of 3x your salary), pension matching up to 6% of qualifying earnings.
- Depop Extras: Employees enjoy free shipping on their Depop sales within the UK. Special milestones are celebrated with gifts and rewards!
Staff Machine Learning Scientist, Ranking 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 Staff Machine Learning Scientist, Ranking
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Depop!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Staff Machine Learning Scientist, Ranking at Depop.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Depop.
✨Apply Directly through Our Website
When you find a suitable opening like Staff Machine Learning Scientist, Ranking at Depop, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Staff Machine Learning Scientist, Ranking
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
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.
