As a world market leader in crop protection, we help farmers to counter these threats and ensure enough safe, nutritious, affordable food for all – while minimizing the use of land and other agricultural inputs. Syngenta Crop Protection keeps plants safe from planting to harvesting. From the moment a seed is planted through to harvest, crops need to be protected from weeds, insects and diseases as well as droughts and floods, heat and cold. Syngenta Crop Protection is headquartered in Switzerland. This role can be in any Syngenta location within EAME As Senior Data Scientist Product Biology CPD EAME you will have complete ownership of data exploration efforts, connecting different data sources and extracting additional value and insights from existing and future data (e.g. trial results, imagery, sensors data). Therefore you will contribute to data analysis and statistics, with ownership of data extraction, processing, analysis reporting, and visualization. You will also contribute to the digital transformation in CPD, exploring new ways of working and new technologies, and innovating data capture and analysis methodologies. In this role, you will work in close collaboration with different functions and stakeholders in EAME, other regions, and global to meet the requirements for data analysis, artificial intelligence, machine learning, predictive analytics, and visualization in a cost-effective way. Independently ensure that good data-science practice is applied in all projects. Closely work with product-line, product biology, and data quality teams in statistical, data analytics, and machine learning work applied to CP projects development Continuously improve data-analysis methods and engines applied in the business in coordination with other team members locally and globally. In coordination with other functions, help in the transition to big-data methods applied to agriculture and trialing-related activities. Provide documentation, training material, and training courses to the end users regarding new tools and data projects deployed by the team. Support the team at the EAME level or globally with new technologies, Data Analytics, and Predictive Modelling activities wherever necessary. Work with key stakeholders and understand their needs to develop new or improve existing solutions around data tools, data analytics, and data modeling. M.Sc. or Ph.D. in statistics, Applied mathematics, Data Science, Machine Learning, computer sciences, or natural sciences (e.g., biology, chemistry, agronomy) Profound knowledge of data-analytics methods and their application in biology, agronomy, and crop protection. Advanced technical knowledge of Python programming language, ideally with experience in package development. Familiar with at least one of the BI tools like Power BI, Spotfire, Tableau, or Click Sense. Power BI knowledge will be a plus. Good knowledge of Big Data technologies and excellent knowledge of Machine/Deep learning algorithms and familiarity with the Python libraries to implement them Agile mindset, with a focus on the delivery of results in constant contact with stakeholders and end users. Familiar with Git or other version-control systems for software development and familiar with database query languages (e.g., SQL). Proven record of good English written and verbal communication skills We offer a variety of financial and non-financial benefits including: We offer a position which contributes to valuable and impactful work in a stimulating and international environment Flexible working arrangements and environment with an open culture and diverse workforce The opportunity to work with and learn from highly qualified and experienced employees Learning culture (Together we Grow) and wide range of training options You will profit from a competitive pension fund plan, attractive bonus system, onsite doctor, gym, canteen, and other benefits (Family friendly initiatives, Child and Family allowance...) Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.