Senior/Principal Data Scientist (m/f/d)

<h2>About Stenon GmbH</h2><p>At Stenon we are on a mission to democratize soil data. We have become the global market leader in real-time, digital soil data. This provides farmers with essential insights to make optimal and sustainable cultivation decisions, boosting yield, crop quality, and soil health while saving money on inputs. Stenon has closed an $18 million Series B financing round to scale real-time nitrogen and soil data management and is expanding internationally.</p><p></p><p><strong>Position</strong></p><p>We seek a versatile and experienced Senior Data Scientist, that drives and expands our existing soil nutrient machine learning as well as new data-driven features that support our customers in making better agronomic decisions for their fields using real-time soil data.</p><p></p><h2>What you will do</h2><ul><li><p>Be responsible for a core pillar of Stenon’s products</p></li><li><p>Scale our soil nutrient modelling to support more and more regions across the world</p></li><li><p>Oversee planning, execution and delivery of Data Science projects.</p></li><li><p>Contribute to the Data Science strategy, vision and roadmap, enhancing Stenon’s agronomy intelligence layer to support additional features and enable new data sources</p></li><li><p><strong>Work with a variety of data from spectral sensor data via chemical lab analysis results to spatial fertilization maps.</strong></p></li></ul><h2>What you must have</h2><ul><li><p>At least <strong>5+ years</strong> of hands-on experience in Data Science products</p></li><li><p>Advanced Degree in <strong>Engineering or Science</strong></p></li><li><p>Exceptional understanding of statistical and <strong>fundamental machine learning concepts</strong></p></li><li><p>Experience writing and maintaining<strong> python code</strong>, incl. common libraries like<strong> scikit, pytorch</strong> as well as ML-Ops infrastructure like <strong>MLflow, DVC</strong></p></li><li><p>High degree of <strong>autonomy</strong></p></li><li><p>Ability to translate <strong>complex statistical</strong> or machine learning concepts<strong> into digestible information</strong> for non-technical audiences</p></li><li><p><strong>Experience across the machine learning product lifecycle</strong>: defining success metrics, model evaluation and validation, deployment, monitoring and iteration, in collaboration with data engineers</p></li><li><p>A strong sense for data and<strong> code quality</strong> and the ability to push for high standards</p></li><li><p>High-dimensional <strong>sensor/signal data</strong> processing expertise</p></li><li><p>Proven track record of managing complex projects from start to finish in a fast paced environment</p></li><li><p>Experience leading or<strong> mentoring team members</strong></p></li><li><p>Good communication and <strong>English language skills</strong> - verbal and written</p></li></ul><p><strong>You may have</strong></p><ul><li><p>Experience in geo-spatial products</p></li><li><p>Knowledge of agronomy or agriculture, sensor/IoT data, or field trials</p></li><li><p>Understanding of sensor hardware, physical measurement principles and real world noise characteristics&