[Hiring] Senior Data Scientist @Syngenta Group

Role Description

Join our global analytics team within Product Biology & Sustainable Innovation and help shape the use of predictive science in Crop Protection R&D. As a Senior Data Scientist – Predictive Science, you will develop machine-learning and predictive-modelling approaches that guide the discovery, optimisation and development of Crop Protection solutions. You will connect diverse scientific data with business and R&D decision-making, working closely with multidisciplinary teams to generate robust insights and accelerate complex decisions. This role offers the opportunity to work autonomously on high-impact scientific challenges, influence modelling approaches and data strategy, and collaborate with experts across an international research environment.

What you will do

• Develop and validate predictive models based on historical, experimental and scientific data to support project and business decisions.
• Partner with multidisciplinary teams to support the discovery, optimisation and development of Crop Protection leads and product candidates.
• Integrate and analyse data from different sources, including physical chemistry, biokinetic, environmental, laboratory, glasshouse and field-trial data.
• Work with scientists to understand complex problems and identify opportunities where predictive modelling can create value.
• Provide guidance on experimental and field-trial design to improve data quality and enable effective modelling.
• Collaborate with R&D IT and software development teams to build data connections and deploy analytical or customer-facing applications.
• Investigate interdisciplinary and multiscale modelling approaches to address scientific challenges.
• Monitor relevant developments across industry, academia and technology providers, assessing new methods and tools for their potential application.
• Collaborate with external partners where relevant, integrating complementary expertise into projects and programmes.
• Contribute to data strategy through the effective connection and use of internal and external scientific data sources.
• Establish and track key performance indicators and success metrics for predictive modelling initiatives to demonstrate business impact.
• Mentor junior data scientists and analysts, fostering a culture of continuous learning and methodological excellence within the team.
• Ensure robust documentation of modelling approaches, assumptions and validation procedures to support reproducibility and knowledge transfer.
• Communicate complex analytical findings to non-technical stakeholders through clear visualisations and executive summaries.

In the first months, you will build strong internal partnerships and Crop Protection domain knowledge, support active-ingredient projects using established modelling methods, and identify opportunities to accelerate the impact of predictive science.

Qualifications

• Advanced academic background in Data Science, Machine Learning, Statistics, Mathematics, Physics or a related quantitative discipline; postgraduate education is strongly preferred.
• Demonstrated experience developing machine-learning or predictive models for biological, scientific, agricultural, life-science or Crop Protection-related outcomes.
• Strong knowledge of Python and relevant data science, analytics and modelling tools.
• Strong understanding of model validation, robustness assessment and the interpretation of predictive-model performance.
• Experience analysing complex datasets and translating findings into clear, actionable insights.
• Experience collaborating with scientists, data scientists or technical specialists to solve complex problems.
• Strong analytical thinking, creative problem-solving and intellectual curiosity.
• Ability to work independently, manage priorities effectively and deliver work to a high standard of accuracy.
• Strong communication skills, including data visualisation and storytelling for specialist and non-specialist audiences.
• Professional proficiency in English.

Requirements

• Academic or professional experience in biology, chemistry, ecology, environmental science, biokinetics or related scientific domains.
• Experience working with laboratory, field-trial, environmental or other complex scientific datasets.
• Experience with interdisciplinary or multiscale modelling approaches.
• Experience collaborating with external partners, vendors, academic institutions, or R&D IT teams on data platforms and analytical applications.

Benefits

• Extensive benefits package including a generous pension scheme, bonus scheme, private medical & life insurance.
• Up to 31.5 days annual holiday.
• Flexible working.
• The opportunity to develop and apply your science within the chemical industry.
• The chance to work as part of a global team to address the current and future needs of the agricultural sector.
• Learning culture and wide range of training options.