- Pricing Engine Optimization: Develop and iterate on bid estimation algorithms and margin-optimization models to power our dynamic pricing engine, directly driving company profitability.
- Carrier Forecasting: Build robust predictive models to forecast carrier behavior and market capacity, enabling our operational teams to secure the right trucks at the right price before the market shifts.
- Recommender Systems: Maintain and improve our existing recommender systems to seamlessly support our operational teams' day-to-day efficiency.
- Industry Innovation & Applied ML: Explore and validate new areas where machine learning can solve fundamental logistics challenges (such as freight routing and network optimization), turning open-ended industry problems into scalable, data-driven solutions.
- Product Discovery & Ideation: Partner closely with Product Managers to drive continuous product discovery, translating ambiguous operational pain points into clear, outcome-driven ML hypotheses and rapid prototypes.
- AI & LLM Integration: Leverage foundational models and AI agents both as daily accelerators for your own engineering workflows and as core components to build new internal products. We expect you to pragmatically evaluate trade-offs and always choose the right solution for the right problem—whether that is an LLM, a traditional ML model, or a simple heuristic.
- Platform Collaboration: Partner with our Data & AI Platform (MLOps) team to utilize and deploy models via our internal ML infrastructure. You will act as a key customer of this platform, providing continuous feedback and contributions to shape our global engineering standards.
- End-to-End Execution: Adopt a holistic approach to project deployment, maintaining an end-to-end attitude that covers the entire lifecycle from initial R&D and prototyping all the way through to production release and monitoring.
- Experience: 5+ years of hands-on experience in Data Science or Machine Learning Engineering.
- Data Science Fundamentals: Strong foundation in statistical analysis, hypothesis testing, and deep data exploration to validate assumptions and commercial viability before building complex models. You must possess a working knowledge of ML approaches to address basic regression and classification problems.
- ML Engineering: Experience deploying models to production environments, writing modular code, and understanding software engineering best practices.
- Technical Skills: Strong proficiency in Python, SQL, and Git. Experience working with cloud data warehouses (e.g., Snowflake), utilizing Jupyter Notebooks for data exploration, and building interactive data apps/dashboards (e.g., Streamlit, PowerBI) to visualize outcomes for stakeholders.
- AI Proficiency: A solid understanding of how to set up, evaluate, and leverage Large Language Models (LLMs) and related AI tools in a production setting.
- Business Acumen: Ability to translate complex & multifaceted logistical problems into data-driven solutions, prioritizing 'Outcome over Output'.
- Collaboration: Strong communication skills to work closely with Product Managers, end-users, and a diverse team of ML Engineers, Data Scientists and Platform Engineers.
- Impact: Build the data and AI foundation for Europe’s leading digital freight platform, at the moment sennder is shifting from buy-and-build to outcome-driven and AI-native.
- Vibrant Workspaces: Our offices are equipped with healthy snacks, focus zones, and social areas to keep you energized and connected. Highlights include a slide in our Wroclaw office and a sunny rooftop terrace in Berlin, Amsterdam, and Milan.
- Culture: Work in a fast-paced, hybrid environment with 1,100 talented, diverse colleagues from 74 nationalities. We prioritize well-being through initiatives like our sennCare program and a partnership with nilo.
- Growth & Rewards: We believe in rewarding our team for their commitment and contributions to our long-term success. Our compensation package may include performance bonuses, referral rewards, or equity that align with our goal of building a thriving company together.
Skills Required
- 5+ years hands-on experience in Data Science or Machine Learning Engineering
- Strong foundation in statistical analysis, hypothesis testing, and deep data exploration
- Working knowledge of ML approaches for regression and classification problems
- Experience deploying models to production, writing modular code, and applying software engineering best practices
- Proficiency in Python, SQL, and Git
- Experience with cloud data warehouses (e.g., Snowflake)
- Familiarity using Jupyter Notebooks for data exploration
- Experience building interactive data apps or dashboards (e.g., Streamlit, PowerBI)
- Practical understanding of setting up, evaluating, and leveraging Large Language Models and related AI tools in production
- Ability to translate logistical problems into outcome-driven, data-driven solutions and collaborate with product and operations stakeholders
What We Do
sennder – Europe’s #1 digital freight-forwarder platform for Full Truck Loads. sennder is a leading digital road freight forwarder in continental Europe, linking large commercial shippers with small freight carriers. With its in-house-developed platform, sennder provides a new level of automation, transparency and efficiency to the European €300 billion road freight market, which until now has been dependent on paper, phone and fax and characterized by multi-layer subcontracting. sennder’s digital connection to over 40,000 trucks allows for almost unlimited capacities, no matter what time of the day. sennder digitalizes the truckload-shipping ecosystem by providing mobile apps to drivers, fleet management tools to carrier managers and logistics management solutions to shippers. Real-time booking, a designated contact person always on hand, as well as precise live tracking, bring full transparency to any logistics supply chain. By integrating directly with the shippers’ Transport Management and Freight Management Systems via APIs and by cutting the multiple middle men, sennder increases efficiency and reduces cost for all stakeholders







