Applied Scientist, Pipeline Data Science for Plant Breeding

Syngenta Seeds; Durham (NC); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Full Benefit Package

401k plan

Paid vacation and holidays

Job summary

Syngenta Seeds is seeking an Applied Scientist to design scalable data pipelines for pipeline data science in plant breeding. The role blends data engineering with analytics to deliver reliable, accessible data for stakeholders.

You will model and mine data, collaborate with IT and applied data science teams, and explore ML frameworks and cloud platforms to advance predictive pipelines within a cutting-edge environment.

Qualifications

• Master’s in Computer Science, Statistics, Applied Mathematics, Quantitative Genetics, or related fields.
• Programming in Python, R, SQL with relational and NoSQL databases.
• Experience with Docker/Kubernetes and ML frameworks (Keras, PyTorch, scikit-learn).

Responsibilities

• Build scalable data pipelines that integrate multiple data sources.
• Ensure data quality, reliability, and accessibility for stakeholders.
• Drive data modeling and mining to support advanced analytics.
• Collaborate with IT, data science teams, and business stakeholders.
• Identify opportunities to apply advanced analytics and cloud platforms.
• Support adoption of genomic prediction methods in breeding processes.

Skills

Programming

Cloud

Analytics

Collaboration

Education

Master’s degree

Tools

Docker

Kubernetes

scikit-learn

Keras

PyTorch

Job description

Syngenta Seeds is seeking an Applied Scientist to design scalable data pipelines for pipeline data science in plant breeding. The role blends data engineering with analytics to deliver reliable, accessible data for stakeholders.

You will model and mine data, collaborate with IT and applied data science teams, and explore ML frameworks and cloud platforms to advance predictive pipelines within a cutting-edge environment.