The Seeds Development department for Syngenta seeks a passionate candidate for a full-time position of: Applied Scientist - Pipeline Data ScienceType: Permanent 
Department: Seeds Development / Vegetables
Location: Durham, NC, USAInto action Do you thrive at the intersection of data engineering, predictive analytics, and innovation? As our Applied Scientist - Pipeline Data Science, you will play a crucial role in designing scalable data solutions that drive actionable insights. By consolidating complex datasets into robust, efficient pipelines, you’ll empower teams to make better decisions and uncover new possibilities in plant breeding. This is your opportunity to work on impactful projects in a collaborative and cutting-edge environment where data drives transformation. The challengeAs an Applied Scientist, you’ll focus on building the infrastructure that makes data accessible, reliable, and actionable for diverse stakeholders. Your key responsibilities will include: Building Scalable Data Pipelines: Design, implement, and optimize data pipelines that integrate and consolidate data from multiple sources, ensuring seamless data flow and availability. Ensuring Data Quality and Reliability: Develop systems to track, monitor, and maintain the quality, consistency, and integrity of data to ensure robust outputs for analysis and decision-making. Driving Data Modeling and Mining: Create and implement processes for advanced data modeling and mining to support innovative analytical approaches. Collaborating Across Teams: Work closely with IT, applied data science teams, and business stakeholders to align data solutions with organizational goals, addressing unique data needs efficiently. Identify opportunities to incorporate advanced analytics, including machine learning frameworks and cloud platforms to continuously improve predictive pipelines.Influence adoption of prediction methods, contribute towards their integration in the breeding process and the transformation of breeding schemes.This role combines creativity and problem-solving with a focus on real-world applications. You’ll not only shape the way data is managed but also contribute to meaningful outcomes in plant breeding and sustainable agriculture. Every dataset you refine and every system you enhance will drive smarter decisions and impactful innovations.