About this role
Hi, we’re Back Market.We’re here to help make tech reliable, affordable, and better than new. We're a global marketplace for refurbished devices, helping lower our collective environmental impact by providing trustworthy, affordable tech with 92% less carbon emissions than new.
Yep, you read that right. Turns out refurbished tech is way better for the planet than new. In fact, With every device purchased on Back Market, our positive impact on the planet grows. From our Customer Care representatives to our software engineer, every individual at Back Market cuts the planet — and consumers — a break. Our mission is simple: to do more with what we already have.
Are you ready to join us?
About the role
As part of the Bureau of Technology, you’ll design, build, and scale AI-driven solutions to improve our Customer Care. You’ll join a new team, Care AI (a mix of data scientists and backend engineers) focused on enhancing the experience of our customers in need of help with faster and more precise resolutions. Your focus will be in implementing and scaling our Care AI agents and improving AI powered features aimed at increasing agents efficiency, detecting customer sentiment and speeding up resolutions.
What you will do
Develop, evaluate and improve AI models powering customer care automation, including conversational AI with FinAI, sentiment analysis, and predictive analytics
Own the data science lifecycle for CSent metric evolution, Help Request Classification improvements, and new AI feature for Care
Conduct experiments and A/B tests to validate AI feature performance and impact on customer satisfaction
Collaborate with backend engineers to productionize models and ensure robust monitoring of AI systems in production
Strong interest in NLP, LLMs, and conversational AI with eagerness to explore emerging technologies (MCP servers, Agent to Agent)
Excited about solving real customer problems and measuring impact through data-driven insights in the care domain
About you
At least 5 years of industry experience as a data scientist and Master’s (or PhD ) in a quantitative discipline such as Statistics, Economics or Engineering
Impact-driven: You’ve contributed to data science projects that made a real impact on live, customer-facing products — not just in theory, but in production.
Strong grasp of machine learning and statistical concepts and know how to choose the right model for the problem and make it work in a production environment.
Practical expertise in experimentation design and analysis.
Proficient in Python and SQL, and familiarity with software engineering principles around testing, code reviews, and deployment.
Clear communicator: You are comfortable explaining complex ideas and results to diverse audiences.
Recruitment process:
Call with one of our Tech recruiter (1h)
Data Science Challenge
Technical Interview (1h15)
Team Fit (1h)
Back Market Values fit interview - 45 min