Junior Data Scientist, Marketplace - Berlin

Location: Come and join us either in Berlin, Barcelona, Athens or Hamburg.

We are looking for a Junior Data Scientist to join our Marketplace team at Freenow. In this role, you will support the development of intelligent pricing and allocation models that enhance the experience for both riders and drivers. You will contribute to the end-to-end lifecycle of machine learning products, helping to transform complex data into real-time decisions that drive user engagement and operational efficiency across our European markets.

YOUR DAILY ADVENTURES WILL INCLUDE:

• Model Development: Assisting in the training and refinement of machine learning models focused on dynamic pricing, allocation, and incentives.

• Marketplace Optimisation: Supporting the design of voucher and incentive strategies using causal modelling to measure and improve user engagement.

• Productionalising Code: Working closely with Machine Learning Engineers to deploy models into production, ensuring scalability and performance.

• Monitoring & Quality: Participating in the maintenance of quality monitoring systems to ensure the ongoing reliability of our real-time ML models.

• Stakeholder Collaboration: Translating technical metrics into clear, actionable insights for product and business managers.

• Technical Innovation: Proactively testing small-scale improvements to existing models and researching GenAI applications

• Experimentation: Generating data-driven insights through forecasting and A/B testing to help the team anticipate emerging marketplace trends.

TO BE SUCCESSFUL IN THIS ROLE:

• Educational Background: You hold a degree (BSc or MSc) in a STEM field such as Physics, Engineering, Mathematics, or Computer Science.

• Data Proficiency: You are proficient in writing and optimising complex SQL/HQL queries to extract and manipulate large-scale datasets independently.

• Programming Skills: You write clean, structured Python code and are comfortable with technical configurations including Git, Docker, and environment management.

• Analytical Mindset: You possess a solid understanding of statistical analysis, probabilistic modelling, and foundational Machine Learning.

• Communication: You have the ability to explain intricate technical concepts to non-technical audiences and use data visualisations to recommend strategy adjustments.

• Continuous Learning: You stay current with industry trends, including an interest in LLMs and generative AI, and are eager to adopt new architectural patterns.

• Bonus Points: Prior experience with Databricks, an enthusiasm for geo-spatial data, or exposure to specialised domains such as Causal Inference, Reinforcement Learning, or Time Series Analysis.

BENEFITS & PERKS IN A NUTSHELL:

• Flexible working arrangements

• LinkedIn Learning

• Sabbatical & special leave policies

• WeRoad partnership

• Birthday, 24th + 31st December off

• Short term EU work policy

• Mobility Credit

• Health Insurance

• Employee assistance program

DIVERSITY, EQUITY & INCLUSION:

FREE NOW is an equal opportunity employer and we consider qualified applicants regardless of race, religion, national origin, gender, gender identity, sexual orientation, disability or age.
We want you to grow and evolve, bring your true self to work.

ABOUT FREENOW:

We are Freenow, the European taxi app with the broadest multi-mobility offering, available in 9 markets and over 180 cities. Our app gives millions of passengers the freedom to move with a wide choice of services including taxis, private hire vehicles, carsharing, car rental, e-scooters, e-bikes, e-mopeds and public transport.Headquartered in Hamburg and led by our CEO Thomas Zimmermann, we are on a mission to make urban mobility more efficient, sustainable and inclusive.Since July 2025 we have been part of Lyft, a global mobility platform connecting riders and drivers for billions of rides across North America and Europe. Together we are building a more caring and connected world, creating new opportunities for innovation, growth and impact.

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