Senior Machine Learning Scientist

Type: Permanent  

Business Unit: Global Data Analytics and Predictive Science Team

We have an exciting opportunity for data scientists specialized in machine learning with interests in agriculture and environment, to join our Global Data Analytics and Predictive Science Team! Within this role you will be working within Global Product Biology and across R&D functions to bring new insights for active ingredient development by developing predictive models, while guiding design, optimization and development of novel crop protection solution. In this role, you will not only apply existing ML approaches but also develop innovative solutions to unique agricultural challenges that haven't been solved before. Responsibilities will include:

• Designing and implementing innovative machine learning solutions to solve complex agricultural and environmental challenges that often require novel approaches.
• Developing and optimizing predictive models using structured historical cross-functional data from field trials, laboratory experiments, and environmental measurements.
• Translating agricultural/environmental problems into data science solutions in collaboration with domain experts.
• Supporting experimental design to ensure data suitability for modeling purposes.
• Working with IT teams on end-to-end ML projects from data preparation to model deployment and monitoring.
• Presenting insights and recommendations to stakeholders across different functions.
• Engaging with high-priority digital transformation projects to understand opportunities to accelerate the impact of data science for predictive field trialing.

What we are looking for?

• PhD in Computer Science, Data Science, Machine Learning, or related field (or M.Sc. with extensive hands-on ML experience).
• Proven experience in developing machine learning models, particularly:
  • Supervised learning (Random Forests, XGBoost, SVM etc.).
  • Clustering and dimensionality reduction.
  • Time series analysis.
  • Handling hierarchical/nested data structures.
• Strong programming skills in Python and experience with ML frameworks (scikit-learn, pandas, etc.).
• Demonstrated ability to develop novel solutions beyond applying existing frameworks.
• Creative problem-solving mindset and ability to think outside standard approaches.
• Experience in adapting and modifying algorithms to suit specific problem requirements.
• Passion for emerging technologies, including Generative AI and other innovative approaches.
• Strong communication skills to explain technical concepts to non-technical stakeholders.
• Ability to visualize and story-tell with data to communicate results to parties with varying levels of technical proficiency.
• Interest in agriculture, environmental science, or related fields.

Desired Qualifications

• Experience with version control (Git) and ML experiment tracking.
• Experience working in cross-functional teams.
• Familiarity with experimental design or statistical analysis.
• Experience with cloud computing platforms (AWS, Azure, etc.) and querying (e.g. SQL).

Additional locations in Europe (Germany, France, Spain, Portugal, Italy, Poland) can be also considered.

Application & Recruitment Process

Take your chance!

Syngenta is proud of its unique culture and the values that are at the heart of it. We also foster a strong learning culture with plenty of opportunities for personal development. Why? Because our work matters! We offer a competitive salary package, flexible working hours and excellent benefits.

If you recognize yourself in the profile and would like to apply for this position, please upload your resume and motivation letter at www.syngenta.com. Due to exceptionally high interest in this position, we will only consider applications that include a covering letter explaining your motivation for the role and outlining your suitability. Upload your CV and write your cover letter in the “Message to the Hiring Team” section on the application page.

Are you ready to grow your career with us?