Senior Data Scientist

Duration: 3-6 months

Must Have Skills:

• Senior-level Data Science / ML ownership — 5+ years
• ETL / data pipelines for ML — 3+ years
• Python + production ML / MVP delivery — 4+ years
• Geospatial / positional / logistics-related data - any exp

About the Project
We are looking for a Senior Data Scientist / ML Engineer to support a Berlin-based logistics technology product company on a data science project focused on building a production-ready MVP.
The project is currently in an early research / proof-of-concept stage. Initial validation has shown that the concept is technically feasible, and the next step is to bring it from research into a usable MVP that can be integrated into the existing product infrastructure.
The solution will use positional / location-based data to identify specific locations and generate insights that help drivers and improve operational efficiency.
This is not a fully isolated greenfield project. The work will be connected to existing internal systems, data pipelines, and infrastructure. Therefore, the ideal candidate should be highly autonomous, senior enough to clarify requirements directly with internal stakeholders, and able to take ownership of the solution with limited day-to-day supervision.

Responsibilities

• Own the data science and ML development work from research validation to a usable MVP.
• Build and improve data pipelines and ETL processes that feed the model.
• Work with positional / geospatial / location-based data.
• Develop, validate, and iterate on ML models that identify relevant locations and generate useful outputs for the product.
• Prepare the model and pipelines to run in production on a scheduled basis.
• Work with internal data, product, and engineering teams to understand available data, infrastructure, constraints, and business requirements.
• Translate high-level product and business goals into technical implementation steps.
• Make technical decisions independently while keeping internal stakeholders aligned.
• Document the solution, assumptions, limitations, and handover materials for the internal team.
• Ensure that the MVP can be further scaled, improved, and integrated into the company’s existing product suite.

Required Experience

• 5+ years of experience in Data Science, Machine Learning, or ML Engineering.
• Strong hands-on experience building ML models from concept to production or MVP stage.
• Experience working with ETL processes, data pipelines, data preparation, and model input pipelines.
• Strong Python experience and common data science / ML libraries.
• Experience working with large datasets and imperfect real-world data.
• Ability to work with positional, geospatial, mobility, logistics, or location-based data.
• Experience deploying or preparing ML models for production usage.
• Strong understanding of model evaluation, iteration, and practical trade-offs between accuracy, speed, and business value.
• Ability to work independently with limited day-to-day guidance.
• Strong ownership mindset: ability to clarify requirements, identify blockers, communicate with stakeholders, and drive the work forward.

Nice to Have

• Experience in logistics, transportation, mobility, route optimization, delivery, or fleet-related products.
• Experience with cloud data infrastructure such as AWS, GCP, or similar.
• Experience with scheduled production pipelines, batch processing, or workflow orchestration tools.
• Experience handing over ML solutions to internal engineering or data teams.
• Previous experience in startup or product-company environments.