Data Scientist - Pricing & Business Modelling

About the role

Foxway, a fast-growing European company in the technology refurbishing sector, is looking for a Data Scientist to work on pricing, inventory and demand modelling, optimization and decision-support tools. The role covers the full data science lifecycle, from understanding the business problem and building models to production deployment, monitoring and continuous improvement.

Key responsibilities

• Design, build and implement machine learning and statistical models to automate pricing and business decisions for refurbished mobile devices, from prototype to production.
• Develop scalable modelling solutions for dynamic pricing, demand forecasting, competitor analysis and other business modelling use cases.
• Collaborate with business, operations and product stakeholders to turn complex requirements into actionable data science solutions.
• Monitor model performance and business outcomes, address data drift or model degradation, and retrain models as needed.
• Build validation and experimentation approaches and make model behaviour and business impact transparent.
• Work cross-functionally with engineering, data and business teams and communicate findings clearly to technical and non-technical stakeholders.

Required profile

• 2-5 years of hands-on experience in Data Science, Machine Learning or a closely related applied modelling role.
• Experience designing and maintaining the lifecycle of machine learning models in production.
• Degree in Data Science, Statistics, Computer Science, Mathematics or another quantitative field, or equivalent practical experience.
• Preferred: experience in pricing, e-commerce, marketplaces, retail or recommerce, and with pricing optimization, price elasticity, demand forecasting, inventory modelling or revenue management.

Required skills

• Proficiency in Python and SQL.
• Common ML libraries such as scikit-learn, LightGBM or XGBoost.
• Solid understanding of statistical analysis, predictive modelling, model validation and feature engineering.
• Preferred: familiarity with AWS, GCP or Azure and Docker, and interest in AI/LLM applications.