Consultant

We are looking for a Data Scientist to build data-driven aftermarket solutions for significant contribution to fleet uptime, revenue and process efficiency by relevant problem definition, PoC's, covering MVP journey for data exploration through model deployment and monitoring. This role involves transforming complex business questions into actionable insights and predictive models.

ABOUT US At Daimler Truck, we change today’s transportation and create real impact together. We take responsibility around the globe and work together as one global team. We drive our progress and success together – everyone at Daimler Truck makes the difference. Together, we want to reduce our carbon footprint, increase safety on and off the track, develop smarter technology and attractive financial solutions. All essential, to fulfill our purpose - for all who keep the world moving. Become part of our global team: You make the difference - YOU MAKE US

Master’s or Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field. 2+ years of experience in data science, machine learning, or advanced analytics. Strong proficiency in Python, R, SQL, and modern data science libraries/frameworks. Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices for deployment and monitoring. Solid understanding of statistical modeling, machine learning algorithms, and data engineering concepts. Ability to translate complex business challenges into data-driven solutions. Strong communication and collaboration skills.

Define relevant business problems and translate them into analytical frameworks. Build and validate PoCs to demonstrate feasibility and value of data-driven solutions. Drive the MVP journey, including data preparation, feature engineering, and model development. Deploy predictive models into production environments and establish monitoring frameworks for performance and reliability. Collaborate with cross-functional teams to ensure solutions align with strategic goals. Continuously refine models and solutions based on new data, feedback, and evolving business needs.