Be responsible for a core pillar of Stenon’s products Scale our soil nutrient modelling to support more and more regions across the world Ov
Gerade starten wir neue Projekte, bei denen wir von Anfang an AI-first denken – von der Entwicklung bis zur Produktidee.
Gerade starten wir neue Projekte, bei denen wir von Anfang an AI-first denken – von der Entwicklung bis zur Produktidee.
CT is a European-based international engineering company with a clear mission: to provide innovative and technological solutions that help o
Introduction HeiGIT (Heidelberg Institute for Geoinformation Technology) As a nonprofit research institute, HeiGIT (Heidelberg Institute for
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will combine hands-on technical exposure with scientific curiosity and business relevance: from extracting insights from client interactions
Use AI as part of the day-to-day data science workflow and identify opportunities to develop reusable AI-enabled tools, skills, or agents th
Leitet Projekte zur Entwicklung und Einführung skalierbarer KI-Lösungen für Fertigung und Operations und steuert dabei internationale Stakeholder.
Lead and develop the Advanced Technologies Team, driving innovation in Data Science, Artificial Intelligence, Machine Learning, and Equipmen
Leitet ein Team, das skalierbare Analysepipelines für Spatial-Omics-Daten entwickelt und agentische KI-Workflows zur Automatisierung von Analysen aufbaut.
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Über das UnternehmenWenn du schon mal eine CAD-Zeichnung gesehen hast und dachtest: „Da steckt doch mehr drin als nur Linien und Maße“, dann
is to provide expert human judgment on whether the resulting research is scientifically valid, genuinely novel, and of a quality comparable
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KAYAK, part of Booking Holdings (NASDAQ: BKNG), is the world s leading travel search engine.
Leitet KI-Projekte vom Konzept bis zum Betrieb beim Kunden, entwickelt Kundenbeziehungen und integriert Voice Agents und Automatisierungen in Unternehmensprozesse.
Warum dieser Job gelistet ist
Eindeutige KI-Rollenbezeichnung im Stellentitel. Prüfverfahren ansehen
Be responsible for a core pillar of Stenon’s products Scale our soil nutrient modelling to support more and more regions across the world Oversee planning, execution and delivery of Data Science projects. Contribute to the Data Science strategy, vision and roadmap, enhancing Stenon’s agronomy intelligence layer to support additional features and enable new data sources Work with a variety of data from spectral sensor data via chemical lab analysis results to spatial fertilization maps. What you
At least 5+ years of hands-on experience in Data Science products Advanced Degree in Engineering or Science Exceptional understanding of statistical and fundamental machine learning concepts Experience writing and maintaining python code, incl. common libraries like scikit, pytorch as well as ML-Ops infrastructure like MLflow, DVC High degree of autonomy Ability to translate complex statistical or machine learning concepts into digestible information for non-technical audiences Experience across the machine learning product lifecycle : defining success metrics, model evaluation and validation, deployment, monitoring and iteration, in collaboration with data engineers A strong sense for data and code quality and the ability to push for high standards High-dimensional sensor/signal data processing expertise Proven track record of managing complex projects from start to finish in a fast paced environment Experience leading or mentoring team members Good communication and English language skills - verbal and written You may have Experience in geo-spatial products Knowledge of agronomy or agriculture, sensor/IoT data, or field trials Understanding of sensor hardware, physical measurement principles and real world noise characteristics ML Ops or Data Engineering knowledge, like Docker, CI/
Ownership & Growth: A key role in a fast-growing scale-up where you own your area of responsibility with flat hierarchies and fast decision-making. Real-World Impact: Design products that go directly into the hands of farmers, solving global food production and climate challenges. Collaborative Culture: Work in a highly productive, international team that values hands-on development and mutual support.
Work-Life Balance: A permanent full-time role offering adaptable schedules to accommodate your lifestyle. Flexible Location: Choose between hybrid or fully remote options across Germany, featuring one mandatory monthly collaboration day in Potsdam for team cohesion and alignment. Remote Setup Support: A dedicated financial allowance to help you optimize your home workspace Learning Budget: Invest in your professional growth with an annual allowance dedicated to courses, conferences, books and certifications Year-End Break: Enjoy a paid company-wide closure between Christmas and New Year to recharge and spend time with loved ones.
Seamless Commuting: Choose between an ABC Berlin/Potsdam travel pass or a Deutschland-Ticket to keep you mobile. Team Spirit: Annual company retreats to warmer climates (last year we went to Gran Canaria), regular social events, and a fully stocked kitchen with coffee, tea, and snacks. Why Us?
We are changing how farmers understand and manage their soil, moving from lab-based analysis to real-time insights directly in the field. We value transparency, ownership, and continuous improvement, and we believe great products come from teams that respect and support each other. We set high standards, reward performance, and foster a positive, constructive feedback culture.
About Stenon GmbH 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. Position 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.
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Zur OriginalanzeigeModelle bauen, trainieren und verbessern: von klassischem Machine Learning über Computer Vision bis zum Feinschliff großer Sprachmodelle.