Senior Data Scientist

Senior Data Scientist (m/f/d) – Machine Learning & AI

Employment Type: Full-time

Drive AI Innovation at Scale:

I'm currently partnering with one of Europe's fastest-growing consumer tech marketplace companies to find a Senior Data Scientist to join a high-impact, product-led Data Science team.

This is a role for someone who enjoys solving complex business problems with machine learning and seeing their work directly influence product decisions, customer experience and commercial performance. You'll own projects end-to-end, collaborating closely with Product, Engineering, Analytics and business stakeholders to deliver measurable impact.

We're particularly looking for candidates with strong expertise in one of the following domains:

• Dynamic Pricing & Revenue Management
• Ranking & Recommendation Systems

You'll Be a Great Fit if You Have:

• 4+ years of commercial Data Science experience
• Strong Python and SQL skills
• Solid experience with classical Machine Learning, statistics and predictive modelling
• Experience owning ML projects from problem definition through deployment and measuring business impact
• Strong stakeholder management and communication skills
• A product and business-first mindset
• Experience working with large-scale datasets in production environments
• The ability to translate ambiguous business challenges into scalable ML solutions

Experience in One or More of the Following Areas Is Highly Desirable:

• Dynamic Pricing
• Revenue Management
• Forecasting
• Ranking
• Recommendation Systems

Your Responsibilities:

• Design, build and deploy scalable machine learning models into production.
• Develop predictive models for pricing, forecasting, ranking, recommendations, churn prediction, customer segmentation and revenue optimisation.
• Analyse large, complex datasets to uncover business opportunities.
• Design, execute and evaluate A/B tests and other online experiments.
• Continuously monitor, improve and retrain production models.
• Partner with Product Managers, Software Engineers, Data Engineers and business stakeholders to deliver measurable outcomes.
• Drive projects from problem definition through deployment and monitoring.
• Contribute to technical strategy, best practices and knowledge sharing within the Data Science organization.