Overview
Applied Scientist in Pipeline Data Science designing scalable data solutions that provide reliable, actionable insights for plant breeding.
What you'll do
- Design, implement, and optimize scalable data pipelines that consolidate data from multiple sources.
- Support data mining, curation, analytics, and visualization to enable crop-related understanding.
- Create and implement advanced data modeling and mining processes for analytical approaches.
- Collaborate with IT, applied data science teams, and business stakeholders to align solutions with data needs.
- Incorporate advanced analytics, including machine learning frameworks and cloud platforms, to improve predictive pipelines.
- Influence adoption and integration of genomic prediction methods in the breeding process.
What you'll need
- Master’s degree in Computer Science, Statistics, Applied Mathematics, Quantitative Genetics, or a related field.
- Programming skills in Python, R, and SQL.
- Experience with relational and NoSQL databases.
- Familiarity with AWS services and infrastructure.
- Ability to uncover patterns in large datasets and translate results into actionable recommendations.
- Ability to communicate technical concepts to diverse stakeholders.
Nice to have
- Experience with Docker/Kubernetes.
- Experience with machine learning frameworks (Keras, PyTorch, scikit-learn).
- Interest in plant breeding or agricultural innovation.
Details
- Department: Seeds Development / Vegetables.
- Locations: Enkhuizen (NL) and RTP (US).
- Employment type: Permanent.
- Hybrid work mode.
- US work authorization required for candidates residing in and permanently authorized to work in the United States without employer sponsorship.
Read the full description and apply on the company’s own careers page.
