Syngenta
Heute veröffentlichtGehöre zu den ersten 5 Bewerbern

Data Scientist (m/f/d)

Stein (AG) · Agrochemie / Pflanzenschutz · Unternehmen · 50,000 · Englisch

Hybrid100%Mid / Senior

Company Description

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.

Job Description

  • 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

Qualifications

  • 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

Fähigkeiten

PythonML / AITest & QARSQLMachine Learning
UNIX/LinuxAIData ScienceBioinformaticsComputational BiologyStatistical ModelingProteomicsMetabolomicsData IntegrationFeature EngineeringNetwork-based Methods

Gehaltsspanne

Auf Anfrage

Dieser Arbeitgeber nennt die Gehaltsspanne im ersten Gespräch.

Syngenta
Der ArbeitgeberSyngenta
Unternehmenstyp
Unternehmen
Unternehmensgrösse
50,000
Teamsprache
Englisch
Branche
Agrochemie / Pflanzenschutz

Kontakt

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.

Standort

Stein (AG)
Reisezeiten ab deiner Adresse: kostenlos registrieren.

Ähnliche Jobs

Adaptyv Bio · Lausanne · 100%
Vor Ort
PythonML / AITest & QApandasnumpybioinformaticsAIdata pipelinesstatistical analysisanomaly detectionQC modelsprotein designsequence-structure dataMLdata infrastructure
Accelleron · Baden · 80-100%
Hybrid
PythonML / AISAPRSQLAzureMicrosoft FabricData LakehouseMLOpsMachine LearningStatisticsComputer VisionSAP ERPSAP BWData EngineeringData GovernanceCloud Analytics
Thomson Reuters · Zug · 100%
Hybrid
ML / AIPythonAINLPMachine LearningInformation RetrievalKnowledge GraphsSemantic ChunkingDocument EnrichmentClassification SystemsInformation ExtractionLLMData ScienceProduction DeploymentDocument AnalysisKnowledge RepresentationEvaluation Frameworks
Lonza · Sitten · 100%
Hybrid
PythonML / AIPyTorchTensorFlowScikit-learnAIMLData ScienceMLOpsDigital TransformationPredictive ModellingOptimization ToolsData EngineeringCheminformaticsBioinformatics
Lonza · Sitten · 100%
Hybrid
PythonML / AIPyTorchTensorFlowScikit-learnAIMLData ScienceMLOpsDigital TransformationPredictive ModellingOptimization ToolsData EngineeringCheminformaticsBioinformatics
ti&m AG · Zürich · 80-100%
Hybrid
PythonML / AIArchitectCloudSQLS3AIMachine LearningModel Context ProtocolEvaluation Driven DevelopmentAI-Evaluation- und Observability-PlattformenVektordatenbankenLarge Language ModelsCloud DeploymentOn-premises DeploymentSoftware Engineering