Data Scientist (m/f/d)

Syngenta Group
Location
Stein, AARGAU, CH
Job Type
Full-time
Posted
November 3, 2026

Job Description

We are seeking a highly skilled Data Scientist (m/f/d) with deep expertise in developing multi-omics data integration and machine learnings methods, to join our Digital & Data Science Group in Biologicals Research. Biologicals research discovers, characterizes, optimizes and produces novel biologicals. Biologicals are derived from nature. They can be naturally occurring microbes, extracts or molecules protecting plants from pests and diseases or improving plant and soil health.

Within this role you will work on Syngenta ‘omics data to identify patterns in product performance and make predictions. You will be asked to develop methods to analyze and interpret the outcome of ‘omics experiments with your analytical skills as well as machine learning approaches. Your work will result in new tools to guide selection, optimization and development of novel Biologicals solutions.

Key responsibilities will include

  • Develop and implement new multi-omics integration strategies (e.g., data harmonization, feature engineering, network-based methods) to strengthen biological interpretation and hypothesis generation
  • Apply and advance machine learning, statistical modeling, and AI approaches to extract insights from complex, high‑dimensional, multi‑omics datasets
  • Curate, quality control, and integrate large scale ’omics datasets, ensuring data integrity, reproducibility, and downstream analytical readiness
  • Evaluate and develop new data analysis tools, validate findings using a trial and iterative approach, and effectively communicate findings to technical and non-technical audiences
  • Identify data needs and provide recommendations to scientists to ensure the quantity and verify the integrity of data used for analyses
  • Work collaboratively to deliver new approaches, share learnings, and drive innovation in digital and data science including technology foresight
  • Work with R&D IT and software developers to deploy predictive model applications tailored to stakeholder needs
  • Support business users with change management initiatives to manage data more effectively
  • MSc or PhD in Data Science, Statistics, Machine Learning, Computational Biology, Bioinformatics, or related field with some experience in natural sciences (e.g. chemical biology, microbiology, ecology, environmental sciences)
  • 3+ years developing multi-omics integration methods for complex biological, biochemical, environmental, or agricultural datasets
  • Strong proficiency in Python and/or R, UNIX/Linux environments, ML frameworks, SQL
  • Experience with proteomics and metabolomics data analysis would be an asset
  • Dynamic personality with passion for innovation and problem-solving

We offer a variety of financial and non-financial benefits including:

  • - A position which contributes to valuable and impactful work in a stimulating and international environment
  • A superb working environment with an open culture and diverse workforce where new ideas are always welcome
  • The opportunity to work with and learn from highly qualified and experienced employees and gain scientific and technical excellence
  • Learning culture (Together we Grow) and wide range of training options
  • You will profit from a competitive pension fund plan, flexible working, attractive bonus system, onsite doctor, fitness room, canteen, and other benefits such as Family friendly initiatives, Child and Family allowance

Please send your complete application with CV, a motivation letter that highlights your motivation and relevant experience for this position, diploma and work certificates (if applicable) in English. Additionally, we welcome access to git repositories showcasing relevant past projects. We will only consider applications that contain CV and motivation letters.

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.

We are seeking a highly skilled Data Scientist (m/f/d) with deep expertise in developing multi-omics data integration and machine learnings methods, to join our Digital & Data Science Group in Biologicals Research. Biologicals research discovers, characterizes, optimizes and produces novel biologicals. Biologicals are derived from nature. They can be naturally occurring microbes, extracts or molecules protecting plants from pests and diseases or improving plant and soil health.

Within this role you will work on Syngenta ‘omics data to identify patterns in product performance and make predictions. You will be asked to develop methods to analyze and interpret the outcome of ‘omics experiments with your analytical skills as well as machine learning approaches. Your work will result in new tools to guide selection, optimization and development of novel Biologicals solutions.

Key responsibilities will include

  • Develop and implement new multi-omics integration strategies (e.g., data harmonization, feature engineering, network-based methods) to strengthen biological interpretation and hypothesis generation
  • Apply and advance machine learning, statistical modeling, and AI approaches to extract insights from complex, high‑dimensional, multi‑omics datasets
  • Curate, quality control, and integrate large scale ’omics datasets, ensuring data integrity, reproducibility, and downstream analytical readiness
  • Evaluate and develop new data analysis tools, validate findings using a trial and iterative approach, and effectively communicate findings to technical and non-technical audiences
  • Identify data needs and provide recommendations to scientists to ensure the quantity and verify the integrity of data used for analyses
  • Work collaboratively to deliver new approaches, share learnings, and drive innovation in digital and data science including technology foresight
  • Work with R&D IT and software developers to deploy predictive model applications tailored to stakeholder needs
  • Support business users with change management initiatives to manage data more effectively
  • MSc or PhD in Data Science, Statistics, Machine Learning, Computational Biology, Bioinformatics, or related field with some experience in natural sciences (e.g. chemical biology, microbiology, ecology, environmental sciences)
  • 3+ years developing multi-omics integration methods for complex biological, biochemical, environmental, or agricultural datasets
  • Strong proficiency in Python and/or R, UNIX/Linux environments, ML frameworks, SQL
  • Experience with proteomics and metabolomics data analysis would be an asset
  • Dynamic personality with passion for innovation and problem-solving

We offer a variety of financial and non-financial benefits including:

  • - A position which contributes to valuable and impactful work in a stimulating and international environment
  • A superb working environment with an open culture and diverse workforce where new ideas are always welcome
  • The opportunity to work with and learn from highly qualified and experienced employees and gain scientific and technical excellence
  • Learning culture (Together we Grow) and wide range of training options
  • You will profit from a competitive pension fund plan, flexible working, attractive bonus system, onsite doctor, fitness room, canteen, and other benefits such as Family friendly initiatives, Child and Family allowance

Please send your complete application with CV, a motivation letter that highlights your motivation and relevant experience for this position, diploma and work certificates (if applicable) in English. Additionally, we welcome access to git repositories showcasing relevant past projects. We will only consider applications that contain CV and motivation letters.

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.

At Syngenta Crop Protection, we're pioneering solutions that safeguard global food security while championing sustainable agriculture. As a world market leader headquartered in Switzerland, we empower farmers with innovative crop protection technologies that defend against nature's toughest challenges. We unite advanced science with digital solutions to develop intelligent crop protection that maximizes yields while minimizing environmental impact. Join our mission of revolutionizing plant protection from seed to harvest.

Syngenta has been ranked as a top employer by Science Magazine, and it has been awarded with the "Friendly Work Space" label to all its Swiss sites.

Frequently Asked Questions

Where is this position located, and what is the work mode?
The job is located in Stein, Aargau, Switzerland. The posting mentions flexible working options, though specific remote or on-site schedules are not detailed.
What are the key responsibilities of this role?
You will develop multi-omics integration strategies and apply machine learning and AI to complex datasets. Responsibilities also include curating large-scale 'omics data, developing data analysis tools, collaborating across teams, working with IT to deploy predictive models, and supporting scientists with data recommendations.
What qualifications and experience are required?
Candidates need an MSc or PhD in Data Science, Computational Biology, Bioinformatics, or a related field, plus 3+ years of experience developing multi-omics integration methods. Proficiency in Python and/or R, UNIX/Linux, ML frameworks, and SQL is required. Experience with proteomics and metabolomics is an asset.
What benefits does Syngenta offer for this role?
Syngenta offers a competitive pension fund plan, flexible working, an attractive bonus system, child and family allowances, an onsite doctor, a fitness room, a canteen, training options, and family-friendly initiatives.
What is the application process and what materials are required?
You must submit your CV and a motivation letter detailing your relevant experience in English; applications missing either will not be considered. You should also include your diploma and work certificates if applicable. Access to git repositories showcasing past projects is welcomed.

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Job Information

Source: manual
AI Relevance: 92/100 (Highly relevant)
Remote Type: onsite
Skills & Tags:
syngenta group machine learning bioinformatics computational biology data science proteomics multi-omics

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