Modeling Scientist - Agriculture

Syngenta Crop Protection; Bracknell; On-site; GBP 80,000 - 100,000; Full time

Job summary

A global agrochemical company seeks a Modelling Scientist to join their Data Analytics team in Bracknell, UK. The successful candidate will create predictive models to enhance development processes in crop protection. Ideal applicants hold a Ph.D. and have experience with Python libraries in scientific modeling. The position offers an extensive benefits package and opportunities for professional growth in a stimulating environment.

Benefits

Generous pension scheme

Bonus scheme

Private medical & life insurance

Flexible working

Wide range of training options

Qualifications

• Strong foundations in data-driven predictive modelling at postgraduate level.
• Experience in main data-science and analytics libraries.
• Scientific knowledge in biology, chemistry, or environmental sciences.

Responsibilities

• Create, train and validate predictive models for R&D.
• Interpret scientific experiments using data modeling.
• Collaborate with experts to understand scientific questions.

Skills

Data-driven predictive modelling

Python libraries (Pandas, SciPy, MatPlotLib)

Biological and (bio)chemical knowledge

Analytical problem-solving

Data visualization

Education

Ph.D. in physics, mathematics or related theoretical sciences

Tools

Pandas

SciPy

MatPlotLib

Job description

Job Description

Position : Modelling Scientist - Agriculture

Location

We could consider candidates based at additional locations within Europe

Application process

Carefully read instructions in "Additional Information" section

We have an exciting opportunity for a Modelling Scientist to join our Global Data Analytics & Predictive Science Team! Within this role you will create, train and validate predictive models to uncover patterns and deliver new data-driven insights for active ingredient development across R&D functions. You will be asked to interpret the outcome of scientific experiments with the help of mechanistic understanding and machine learning / deep learning approaches. Your work will bring forward our understanding of biological performance in crop protection and guide design, optimization and development of novel crop protection solutions. Key responsibilities will include :

• Interacting with domain experts to understand scientific questions and identifying modelling opportunities to drive business value;
• Driving strategic business initiatives across Crop Protection R&D by interpreting physical chemistry, biokinetic and environmental data to support decision taking and design laboratory, glasshouse and field trials;
• Guiding technical managers in designing field trials aimed at validating scientific hypotheses and model predictions;
• Working with R&D IT and software developers to improve data-models integration and to deploy applications tailored on shareholders’ needs;
• Monitoring and exploring new modelling approaches, analytical tools and methodologies;
• Engaging with high-priority digital transformation projects to understand opportunities to accelerate the impact of data science for predictive field trialing;

Working with colleagues and external collaborators understanding their complementary capabilities and integrating them into projects and initiatives.

What we are looking for

• Strong foundations in data-driven predictive modelling at postgraduate level (Ph.D. in physics, mathematics or related theoretical sciences);
• Years of experience in the use of the main data-science, -analytics, modelling and visualization Python libraries (Pandas / Polars, SciPy, MatPlotLib);
• Scientific domain knowledge in related fields such as biology, (bio)chemistry, environmental sciences;
• Prior experience in developing models relevant to biological or crop protection outcomes (e.g. ecological modelling, ecotoxicology, environmental fate, epidemiology, disease modelling, PKPD) is a plus;
• Knowledge of data analysis and extracting data insights and new understanding, while communicating scientific and data concepts to specialist and non-specialist audiences;
• Adaptability to different business challenges and data types / sources and to learn and utilize a range of different analytical tools and methodologies;
• Ability to visualize and story-telling with data to communicate results to shareholders with different levels of technical proficiency;
• Analytical problem-solving skills with innovative thinking, while effectively collaborating across diverse teams and managing multiple priorities in a multicultural scientific environment.

Additional Information

Application process

Due to exceptionally high interest in this position, we will only consider applications that include : (1) a CV , (2) a cover letter explaining your motivation and suitability for the role, and (3) a one-page document in which you tell us how (with which tools and algorithms, following which strategy) you would start exploring a 13Kb CSV dataset containing efficacy field trial results for a novel crop protection product including assessments for multiple crop types, trial sites and weather conditions.

Please upload your CV, your cover letter and the one-page document in separate files named “CV_Your-Name", “Cover_Letter_###", and “Answer_###", replacing ‘###’ with your family name.

Our site

We could consider candidates based at additional locations within Europe. You may be required to travel to international R&D locations and to work with collaborators globally.

What we offer

• Extensive benefits package including a generous pension scheme, bonus scheme, private medical & life insurance (depends on the contracting country).
• Flexible working.
• A position which contributes to valuable and impactful work in a stimulating and international environment.
• Learning culture and a wide range of training options.

Syngenta has been ranked as a top 5 employer and number 1 in agriculture by Science Magazine for the 8th consecutive year.