About 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. Our mission is simple: to do more with what we already have.
About the role
As part of the Bureau of Technology, you’ll design, build, and scale AI-driven solutions to improve our marketplace. You’ll join the Pricing & Quality team (a mix of data scientists and backend engineers) focused on curating offers to give customers the best value for money. Your focus will be to implement models and algorithms to optimize fees and pricing.
What You’ll do
- Drive pricing intelligence: design and implement Machine Learning models and optimization algorithms that directly fuel a comprehensive suite of pricing levers.
- Own projects end to end: from problem definition and metrics design, through data extraction and model implementation, to presenting results to business and product stakeholders.
- Collaborate with data scientists and backend engineers to translate models into production-ready features.
- Design and analyze experiments to measure the impact of fee strategies or model changes.
- Leverage statistical analyses to uncover actionable insights and inform critical tech, business and product decisions.
- Communicate your work clearly to engineering, product, and business stakeholders.
At Back Market, you’ll enjoy impact-driven work with hands-on career development in an innovative, driven, and fast-paced environment — with benefits to match, like:
- A mission driven work environment where your day to day makes an impact on the planet.
- Hybrid work environment, with 2 remote days a week and 1 remote work week per quarter, plus 3 flex days.
- Employee Resource Groups, including mentorship programs, comprehensive accessibility policies, and cultural competency training.
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.
- Comfortable with ambiguity: you are able to make decisions and propose directions even when the problem is not fully defined or the data is imperfect.
- 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, including senior management.
- Experience in pricing, B2C marketplaces or revenue management is a strong plus.
