Senior Data Scientist

Job Summary

We are seeking a highly motivated Data Scientist to contribute to the development of robust data foundations and drive analytics and AI initiatives in the domain of machine data. This role is integral to fostering data-driven decision-making across engineering functions, enhancing product quality, optimizing processes, and driving innovation. You will collaborate with cross-functional teams to analyze data, uncover insights, and automate insights delivery across the machine product life cycle. Key areas of focus include providing analytics support and developing predictive AI models for product concepts, development, validation, test design, part specifications, issue detection and resolution, performance optimization, machine maintenance and approval strategies, as well as streamlining development workflows.

Job Responsibilities

Data Management and Analysis: Extract, clean, and analyze large datasets from diverse sources, including telemetry data, test fleet data, and test bench data, to support engineering and AI applications in the agricultural machinery domain. Insight Generation: Identify patterns, trends, and correlations in data to derive actionable insights that inform product development, parts design, specifications, and operational decisions. Cross-Functional Collaboration: Work closely with cross-functional teams to drive data-driven decision-making and foster innovative solutions that enhance engineering efficiency, improve product quality, and enable the development of new, data-driven solutions for product usage. Model Development and Refinement: Continuously develop, evaluate, and refine analytical models and methods to ensure their accuracy, scalability, and relevance to business needs. Machine Learning Applications: Develop machine learning models to predict maintenance needs, optimize machine settings, analyze customer usage patterns, and enhance overall product performance.

Minimum Qualifications

7+ years of experience working with structured data, including cleaning, manipulating, and data mining. Experience with unstructured data is a plus. Proven experience with at least two of the following: statistical models, machine learning, deep learning (preferably time series or large language models for NLP, topic modeling, or conversational AI). Familiarity with model setup, fine-tuning, evaluation, and deployment. Strong proficiency in Python, SQL, PySpark, and common frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Familiarity with R is a plus. Experience with cloud-based tools like Apache Spark, Databricks, AWS Glue, and Amazon SageMaker. Strong data visualization skills and experience with BI tools (e.g., Dash, Tableau, Shiny). Strong communication skills (written, verbal, presentation). Interest in modern agriculture and agricultural machinery is a plus. Strong English skills; German is a plus.