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- Tasks: Create and validate predictive models to drive innovation in crop protection.
- Company: Join Syngenta, a leader in agricultural innovation with a global impact.
- Benefits: Enjoy flexible working, extensive benefits, and a culture of learning.
- Why this job: Make a real difference in sustainable agriculture while advancing your career.
- Qualifications: Ph.D. in relevant fields and experience with data science tools required.
- Other info: Collaborate globally and engage in exciting digital transformation projects.
The predicted salary is between 36000 - 60000 £ per year.
Syngenta Crop Protection is a leader in agricultural innovation, bringing breakthrough technologies and solutions that enable farmers to grow productively and sustainably. We offer a leading portfolio of crop protection solutions for plant and soil health, as well as digital solutions that transform the decision-making capabilities of farmers. Our 17,900 employees serve to advance agriculture in more than 90 countries around the world. Syngenta Crop Protection is headquartered in Basel, Switzerland, and is part of the Syngenta Group. Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. Join us and help shape the future of agriculture!
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 storytelling 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:
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.
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 top 5 employer and number 1 in agriculture by Science Magazine for the 8th consecutive year.
Modeling Scientist - Agriculture in Bracknell employer: Syngenta
Contact Detail:
Syngenta Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Modeling Scientist - Agriculture in Bracknell
✨Tip Number 1
Network like a pro! Reach out to professionals in the agriculture and data science fields on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive modelling projects. Use GitHub or a personal website to display your work with Python libraries like Pandas and Matplotlib. This will give potential employers a taste of what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with data analysis and how you’ve tackled complex problems. Practice explaining your projects in a way that’s easy for non-specialists to understand.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Make sure to follow the application instructions carefully, and don’t forget to tailor your cover letter to highlight your passion for agricultural innovation and data-driven insights.
We think you need these skills to ace Modeling Scientist - Agriculture in Bracknell
Some tips for your application 🫡
Read the Job Description Carefully: Before you start writing, make sure to thoroughly read the job description. It’s packed with clues about what Syngenta is looking for, so tailor your application to highlight how your skills and experiences align with their needs.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background makes you a perfect fit. Don’t forget to mention specific projects or experiences that relate to the modelling and data analysis aspects of the job.
Showcase Your Technical Skills: Since this role involves predictive modelling and data analysis, be sure to highlight your experience with relevant tools and libraries like Python, Pandas, and SciPy. Give examples of how you've used these in past projects to demonstrate your expertise.
Follow Application Instructions to the Letter: Syngenta has specific requirements for the application process, so make sure you follow them exactly. Upload your CV, cover letter, and one-page document as separate files with the correct naming format. This attention to detail shows you’re serious about the opportunity!
How to prepare for a job interview at Syngenta
✨Know Your Models Inside Out
Make sure you can discuss your predictive modelling experience in detail. Be prepared to explain the algorithms you've used, why you chose them, and how they apply to agricultural data. This will show your depth of knowledge and passion for the field.
✨Understand the Business Context
Research Syngenta's role in agriculture and how your work as a Modelling Scientist can drive business value. Familiarise yourself with their crop protection solutions and think about how your skills can contribute to their goals. This will help you align your answers with their mission.
✨Prepare for Technical Questions
Expect questions that test your analytical problem-solving skills. Brush up on your knowledge of Python libraries like Pandas and SciPy, and be ready to discuss how you would approach analysing the provided CSV dataset. Practising with similar datasets can give you an edge.
✨Showcase Your Communication Skills
Since you'll need to communicate complex scientific concepts to various audiences, practice explaining your past projects in simple terms. Highlight your ability to visualise data and tell a story with it, as this is crucial for engaging stakeholders with different technical backgrounds.