Senior Machine Learning Scientist
depopDenver (CO)
Senior Machine Learning Scientist
Posted today
depopDenver (CO)
SENIORITY
Senior
About the role
Senior Machine Learning Scientist 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: You will:
- 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
- QualificationsSkills 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
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 PySparkExperience working with AWS or another cloud platform (GCP/Azure)
Additional Information:
- Health + Mental WellbeingPMI and cash plan healthcare access with Bupa
- Subsidised counselling and coaching with Self SpaceCycle 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 employeesIVF 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 AvivaDepop Extras:
In-office Depop Shop (that's free!) and a packing station with free delivery.
Special milestones are celebrated with gifts and rewards!
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.