Data Scientist II GenAI
London, United Kingdom
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingYou will work alongside scientists across biology, chemistry and environmental disciplines, translating complex scientific questions into practical analytical solutions.
Develop predictive models using historical and experimental data to support decisions across Crop Protection R&D.
Partner with scientific domain experts to identify high-value data science opportunities and translate them into practical analytical solutions.
From the employer’s posting
Job Description Join our global analytics team within Product Biology & Sustainable Innovation, where we use data, modelling and emerging AI technologies to accelerate scientific decision-making in Crop Protection. As a Mid Data Scientist – GenAI, you will develop and apply machine-learning and statistical modelling approaches to build a deeper understanding of biological performance. You will work alongside scientists across biology, chemistry and environmental disciplines, translating complex scientific questions into practical analytical solutions. You will also help explore and apply generative AI, large language models, agentic workflows and knowledge graphs to scientific use cases. This is an opportunity to contribute to meaningful R&D initiatives whilst building expertise in responsible AI and predictive science within a highly collaborative, international environment. What you will do
What you will do Develop predictive models using historical and experimental data to support decisions across Crop Protection R&D. Prepare, integrate and analyse heterogeneous datasets from internal and external sources, ensuring data quality and integrity throughout the analytical pipeline.
Prepare, integrate and analyse heterogeneous datasets from internal and external sources, ensuring data quality and integrity throughout the analytical pipeline. Partner with scientific domain experts to identify high-value data science opportunities and translate them into practical analytical solutions. Support the design of experiments and field trials to enable effective modelling and analysis.
What you’ll bring
All qualificationsCore experience
- Master's degree in Data Science, Computer Science, Statistics, Mathematics, Physics, or a quantitative natural science; equivalent practical experience will also be considered.
- 1–4 years of relevant professional or research experience; internships, academic projects and thesis work may be considered.
- Proficiency in Python for data science and machine learning, including libraries such as 'pandas', 'scikit-learn', 'PyTorch' or 'TensorFlow'.
- Experience cleaning, integrating and preparing complex or heterogeneous datasets for analysis.
- Familiarity with software engineering best practices, including Git, testing, documentation and reproducible workflows.
- Ability to collaborate with scientists or domain experts and communicate insights clearly to both technical and non-technical audiences.
Qualification wording
Master's degree in Data Science, Computer Science, Statistics, Mathematics, Physics, or a quantitative natural science; equivalent practical experience will also be considered.
1–4 years of relevant professional or research experience; internships, academic projects and thesis work may be considered.
Proficiency in Python for data science and machine learning, including libraries such as 'pandas', 'scikit-learn', 'PyTorch' or 'TensorFlow'.
Experience cleaning, integrating and preparing complex or heterogeneous datasets for analysis.
Familiarity with software engineering best practices, including Git, testing, documentation and reproducible workflows.
Ability to collaborate with scientists or domain experts and communicate insights clearly to both technical and non-technical audiences.
Tools in this posting
- Python
- AWS
- Azure
- Neo4j
- pandas
- scikit-learn
- PyTorch
- TensorFlow
Source — Tool mentions in context
- Strong foundation in machine learning, statistical modelling, experimental design and model validation. - Proficiency in Python for data science and machine learning, including libraries such as 'pandas', 'scikit-learn', 'PyTorch' or 'TensorFlow'. - Experience cleaning, integrating and preparing complex or heterogeneous datasets for analysis.
- Experience with knowledge graphs, 'Neo4j', 'Cypher', 'SPARQL' or graph-based data structures. - Familiarity with AWS or Azure and basic deployment of ML models or data pipelines. - Background or interest in biology, chemistry, environmental science, Crop Protection or other life-science domains.
- Familiarity with LLMs, embeddings, prompt engineering, retrieval-augmented generation and agentic AI frameworks such as 'LangChain', 'LangGraph', 'LlamaIndex' or 'CrewAI'. - Experience with knowledge graphs, 'Neo4j', 'Cypher', 'SPARQL' or graph-based data structures. - Familiarity with AWS or Azure and basic deployment of ML models or data pipelines.
Benefits in the posting
Full benefits wording- Extensive benefits package including a generous pension scheme, bonus scheme, private medical & life insurance.
From the employer’s posting.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 24, 2026 · 52d ago
- Recorded sightings
- 399
- Last seen by us
- Oct 15, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Job description
Job Description
Join our global analytics team within Product Biology & Sustainable Innovation, where we use data, modelling and emerging AI technologies to accelerate scientific decision-making in Crop Protection. As a Mid Data Scientist – GenAI, you will develop and apply machine-learning and statistical modelling approaches to build a deeper understanding of biological performance. You will work alongside scientists across biology, chemistry and environmental disciplines, translating complex scientific questions into practical analytical solutions. You will also help explore and apply generative AI, large language models, agentic workflows and knowledge graphs to scientific use cases. This is an opportunity to contribute to meaningful R&D initiatives whilst building expertise in responsible AI and predictive science within a highly collaborative, international environment.
What you will do
- Develop predictive models using historical and experimental data to support decisions across Crop Protection R&D.
- Prepare, integrate and analyse heterogeneous datasets from internal and external sources, ensuring data quality and integrity throughout the analytical pipeline.
- Partner with scientific domain experts to identify high-value data science opportunities and translate them into practical analytical solutions.
- Support the design of experiments and field trials to enable effective modelling and analysis.
- Prototype and iterate on GenAI applications, including retrieval-augmented generation (RAG), literature knowledge extraction, summarisation and AI-assisted research workflows.
- Build and work with knowledge graphs to structure scientific relationships and provide grounded context for AI-driven reasoning.
- Develop agentic workflows that combine LLMs with tools, databases and APIs to automate multi-step scientific tasks.
- Support the evaluation, validation and governance of AI-powered tools, ensuring outputs are reliable, scientifically sound and appropriate for human decision-making.
- Work with R&D IT and software engineering teams to build data connections and deploy analytical tools or applications.
- Contribute to the development and documentation of data governance frameworks and best practices for responsible AI implementation within scientific workflows.
- Participate in knowledge-sharing initiatives, including documentation of methodologies, lessons learned and recommendations for future analytical projects.
- Keep up to date with developments in data science, machine learning and GenAI, assessing their practical value for scientific workflows and sharing insights with the broader team.
- In your first months, you will build Crop Protection domain knowledge, contribute to active projects using established analytical methods, and deliver one or two initial use cases that demonstrate measurable value.
Qualifications
**Essential**
- Master's degree in Data Science, Computer Science, Statistics, Mathematics, Physics, or a quantitative natural science; equivalent practical experience will also be considered.
- 1–4 years of relevant professional or research experience; internships, academic projects and thesis work may be considered.
- Strong foundation in machine learning, statistical modelling, experimental design and model validation.
- Proficiency in Python for data science and machine learning, including libraries such as 'pandas', 'scikit-learn', 'PyTorch' or 'TensorFlow'.
- Experience cleaning, integrating and preparing complex or heterogeneous datasets for analysis.
- Familiarity with software engineering best practices, including Git, testing, documentation and reproducible workflows.
- Strong analytical and critical-thinking skills, with the ability to evaluate AI outputs rather than simply apply solutions.
- Ability to collaborate with scientists or domain experts and communicate insights clearly to both technical and non-technical audiences.
- Professional proficiency in English.
**Preferred**
- Familiarity with LLMs, embeddings, prompt engineering, retrieval-augmented generation and agentic AI frameworks such as 'LangChain', 'LangGraph', 'LlamaIndex' or 'CrewAI'.
- Experience with knowledge graphs, 'Neo4j', 'Cypher', 'SPARQL' or graph-based data structures.
- Familiarity with AWS or Azure and basic deployment of ML models or data pipelines.
- Background or interest in biology, chemistry, environmental science, Crop Protection or other life-science domains.
Additional Information
Site Details
Jealott's Hill International Research Centre UK is situated in pleasant semi-rural surroundings between Bracknell and Maidenhead and is the place of work for approximately 800 Syngenta scientists and support staff. Jealott’s Hill is one of the main global research and development sites and key activities include research into discovery of new active ingredients, new formulation technologies, product safety and technical support of our product range.
What we offer
Extensive benefits package including a generous pension scheme, bonus scheme, private medical & life insurance.
Up to 31.5 days annual holiday.
Flexible working
We offer a position which contributes to valuable and impactful work in a stimulating and international environment.
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.
Syngenta has been ranked as a top 5 employer and number 1 in agriculture by Science Journal.
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. Learn more about our D&I initiatives here: https://www.syngenta.com/careers/working-syngenta/diversity-and-inclusion
Company Description
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.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on jobs.smartrecruiters.com. The employer’s form will show what is required.
Already applied? Track this application
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
London, United Kingdom
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.