{"id":2120318,"url":"https://alion.io/job/depop-senior-machine-learning-scientist","title":"Senior Machine Learning Scientist","company":{"id":51473,"name":"Depop","domain":"depop.com","url":"https://alion.io/company/depop","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":["GB"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":96000,"max_usd":178000,"period":"year","method":"role_seniority_country_cell","sample_n":39},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Gemini","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"A/B Testing","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Databricks","optional":true},{"name":"GCP","optional":true},{"name":"pySpark","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-30T00:00:00Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-11T01:39:44Z","board_verified":true,"closed_at":null,"days_open":11,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":11},"description":"Company Description\nDepop 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.\nFounded 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.\nPowered 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\nWe 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.\nWe’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.\nAI 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.\nIf, 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 .\nRole\nDepop 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.\nAs 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.\nResponsibilities\nYou will:\nResearch, 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\nLead efforts to productionise and scale these models, partnering with ML and backend engineers so they run reliably on our systems\nIdentify and define requirements from multiple stakeholders across Pricing and Shipping, and lead the design of machine learning solutions to solve applied business problems\nSet up and conduct large-scale experiments to test hypotheses and guide model and product improvements, ensuring statistical rigour and real-world applicability\nKeep 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\nParticipate in team ceremonies, such as technical whiteboarding sessions, planning, and roadmapping\nCommunicate technical findings clearly and confidently to both technical and non-technical audiences\nQualifications\nSkills and Experience\nSignificant experience working as a Machine Learning Scientist, with a proven track record of delivering and scaling models that solve complex, real-world problems\nDeep understanding of machine learning concepts and experience applying them in production settings, using frameworks such as PyTorch, TensorFlow, or gradient boosting libraries\nExperience with causal inference, uplift modelling, or optimisation under constraints, and comfort reasoning about decisions rather than predictions alone\nStrong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles\nAbility to lead end-to-end ML projects, work independently in ambiguous problem spaces, and mentor junior team members\nStrong collaboration and communication skills, with experience aligning technical approaches with cross-functional teams and stakeholders\nBonus Points\nExperience with pricing models, promotions or incentive allocation, or revenue optimisation\nExperience with experiment design and conducting A/B tests\nExperience with bandits, reinforcement learning, or other explore-exploit approaches\nExperience with Databricks and PySpark\nExperience working with AWS or another cloud platform (GCP/Azure)\nAdditional Information\nHealth + Mental Wellbeing\nPMI and cash plan healthcare access with Bupa\nSubsidised counselling and coaching with Self Space\nCycle to Work scheme with options from Evans or the Green Commute Initiative\nEmployee Assistance Programme (EAP) for 24/7 confidential support\nMental Health First Aiders across the business for support and signposting\n\nWork/Life Balance:\n25 days of annual leave with the option to carry over up to 5 days\nImpact hours: Up to 2 days of additional paid leave per year for volunteering\nFully 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.\nFlexible Working: MyMode hybrid-working model with Flex, Office-Based, and Remote options *role-dependent\nAll offices are dog-friendly\nFamily Life:\nFor birth parent: 20 weeks of paid parental leave for full-time regular employees\nFor non-birth parents: 12 weeks of paid parental leave for full-time regular employees \nIVF leave, shared parental leave, and paid emergency parent/carer leave\nLearn + Grow:\nTwice-yearly development chats and yearly performance reviews\nLearning budget\nUpskilling our employees with company-wide training workshops, materials and resources\nYour Future:\nLife Insurance (financial compensation of 3x your salary)\nPension matching up to 6% of full base salary with Aviva\nDepop Extras:\nIn-office Depop Shop (that’s free!) and a packing station with free delivery.\nSpecial milestones are celebrated with gifts and rewards!","description_format":"text","description_chars":6829,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Annual leave","Flexible schedule","Life insurance","Parental leave"],"hiring_locations":[{"name":"United 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