At a Glance
- Tasks: Analyse agricultural data to uncover insights and drive innovation in crop protection.
- Company: Join Syngenta, a top employer in agriculture, known for its inclusive culture.
- Benefits: Enjoy flexible working, generous benefits, and a commitment to your professional growth.
- Other info: Collaborate globally and engage in exciting digital transformation projects.
- Why this job: Make a real impact on global agriculture while working with cutting-edge data science techniques.
- Qualifications: Postgraduate level data science knowledge with experience in Python and machine learning.
The predicted salary is between 30000 - 50000 £ per year.
We have an exciting opportunity for Data Scientists to join our Global Data Analytics & Predictive Science Team in the Product Biology department. Within these roles you will work on Syngenta historical biological data to uncover patterns and deliver new data‑driven insights for active ingredient development across R&D functions. You will be asked to analyse and interpret the outcome of scientific experiments with your analytical skills as well as machine learning approaches. Your work will bring forward our understanding of biological performance in crop protection and guide design optimisation and development of novel crop protection solutions.
Location: 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.
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 100MB CSV dataset of 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___, CoverLetter___ and Answer___, replacing ___ with your family name.
Responsibilities:
- Driving historical data analysis of biological field trials by identifying patterns and analysing the impact of key factors, including product formulations, rates, mixtures, agricultural practices and environmental conditions, on product performance.
- Supporting domain experts in understanding product performance and identifying analytics opportunities to drive business value.
- Contributing to strategic business initiatives across Crop Protection R&D by interpreting physical chemistry, biokinetic, formulation, marketing and environmental data to support decision‑making 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‑model integrations and to deploy applications tailored to 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 to understand their complementary capabilities and to integrate them into projects and initiatives.
Qualifications:
- Strong foundations in data science at postgraduate level with applications in natural sciences (e.g., biology, ecology, environmental sciences).
- Proven experience in the use of the main data‑science, analytics, modelling and visualization Python libraries, including machine‑learning and deep‑learning ones.
- Scientific domain knowledge in related fields such as environmental sciences or biology.
- Prior experience in developing machine‑learning models relevant to biological or crop protection outcomes.
- Hands‑on experience leveraging generative AI (genAI) approaches for data exploration, model development or research acceleration 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 visualise and story‑tell 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:
What we offer: Extensive benefits package including a generous pension scheme, bonus scheme, private medical and 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. Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, colour, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability or any other legally protected status.
Key Skills: Laboratory Experience, Immunoassays, Machine Learning, Biochemistry, Assays, Research Experience, Spectroscopy, Research & Development, cGMP, Cell Culture, Molecular Biology, Data Analysis Skills.
Employment Type: Full‑time
Data Scientist - Agriculture in Bracknell employer: Syngenta Group
Syngenta-Group is an excellent employer, offering a dynamic work environment in Cambridge where innovation meets sustainability. Employees benefit from a comprehensive package that includes extensive training and professional development opportunities, fostering a culture of growth and collaboration. With a commitment to compliance and excellence in crop protection, working here means being part of a team that makes a meaningful impact on agriculture and the environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Agriculture in Bracknell
✨Tip Number 1
Network like a pro! Reach out to people 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
Prepare for those interviews! Research common data science interview questions, especially those related to machine learning and data analysis. Practice explaining your thought process clearly, as you’ll need to communicate complex ideas simply to both technical and non-technical audiences.
✨Tip Number 3
Show off your skills with a portfolio! Create a GitHub repository or a personal website showcasing your projects, especially those related to agricultural data. This gives potential employers a taste of what you can do and how you approach problem-solving.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Tailor your CV and cover letter to highlight your relevant experience in data science and agriculture, and make sure to follow the application instructions to the letter.
We think you need these skills to ace Data Scientist - Agriculture in Bracknell
Some tips for your application 🫡
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Make sure to explain why you're excited about the Data Scientist role in Agriculture and how your skills align with what we're looking for. Be genuine and let your passion for data science and agriculture come through.
Showcase Your Analytical Skills:In your one-page document, dive into the specifics of how you'd tackle that 100MB CSV dataset. Mention the tools and algorithms you’d use, and outline your strategy clearly. This is your opportunity to demonstrate your analytical prowess and creativity!
Tailor Your CV:When updating your CV, make sure it highlights relevant experience and skills that match the job description. Use keywords from the listing to ensure we see how you fit into our team. Remember, clarity and relevance are key!
Follow Our Application Guidelines:We’re super keen on organisation, so please upload your CV, cover letter, and one-page document as separate files named correctly. This shows us you can follow instructions and pay attention to detail, which is crucial in data science!
How to prepare for a job interview at Syngenta Group
✨Know Your Data Science Tools
Make sure you’re well-versed in the key Python libraries for data science, especially those related to machine learning and deep learning. Be ready to discuss how you've used these tools in past projects, particularly in relation to biological data analysis.
✨Prepare Your One-Page Document
This is your chance to shine! Clearly outline your strategy for exploring the 100MB CSV dataset. Mention specific algorithms and tools you would use, and be prepared to explain your thought process during the interview. This shows your analytical skills and your ability to communicate complex ideas.
✨Understand the Business Context
Familiarise yourself with Syngenta’s goals in crop protection and how data science plays a role in achieving them. Being able to connect your technical skills to real-world applications will impress the interviewers and demonstrate your understanding of the industry.
✨Practice Communicating Your Insights
You’ll need to convey your findings to both technical and non-technical audiences. Practice explaining your past projects and results in simple terms, focusing on the impact of your work. This will help you stand out as someone who can bridge the gap between data science and business needs.
