The Role

• Take ownership of the entire ML lifecycle, from exploratory data analysis and model development to production pipelines and ongoing evaluation
• Work hands-on, shaping the data-driven intelligence as the first ML hire on the team
• Collaborate closely with Product and Engineering using a rapid prototyping approach to validate hypotheses and iterate on models
• Extract insights from data and turn them into real product decisions, with maximum creative freedom
• Calibrate models for a growing, heterogeneous customer base and continuously improve model quality
• Work with modern IT architecture and smart solutions for complex damage processes
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What You'll Need

• Several years of experience as a Machine Learning Engineer, Data Engineer, or Applied Data Scientist with a clear engineering focus
• Strong Python and SQL skills, plus confident use of a cloud platform (AWS, GCP, or Azure)
• Solid statistical foundation beyond sklearn defaults, understanding classical and probabilistic model families
• Experience with production model deployment and MLOps fundamentals, able to build new model pipelines from scratch
• Pragmatic, hands-on mindset, enjoying rapid prototyping and delivering MVPs
• Ability to handle incomplete data and shifting requirements with confidence