Applied Genetics Scientist - Pipeline Data Science at Syngenta Group

Durham, North Carolina, United States -

Full Time

Start Date

Immediate

Expiry Date

07 Jun, 26

Salary

0.0

Posted On

09 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, R, SQL, Relational Databases, NoSQL Databases, AWS, Data Mining, Data Curation, Analytics, Visualization, Data Modeling, Machine Learning, Docker, Kubernetes, PyTorch, Scikit-learn

Industry

Farming

Description

Company Description About Syngenta At Syngenta Seeds Field Crops, we're shaping the future of agriculture and empowering farmers to meet the ever-growing demand for food and fuel. We’re a global Ag Tech powerhouse, headquartered in the United States, with passionate, local experts collaborating with farmers to deliver solutions that create market opportunities. We unite precision breeding, advanced biotechnology trait choice, and digital platforms for unmatched in-field performance. Our seeds help mitigate risks such as disease, insect, weed, and extreme weather pressures, all while promoting sustainable farming practices that protect and enhance our planet. Join our mission of revolutionizing food security and transforming agriculture. Job Description Applied Scientist - Pipeline Data Science Type: Permanent Department: Seeds Development / Vegetables Location: Enkhuizen – NL, RTP - US Into 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 challenge As 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: Contribute to data mining, curation, analytics and visualization of data sets to gain deep understanding of the crop(s) and enable successful application of technology 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 genomic prediction methods, contribute towards their integration in the breeding process and the transformation of respective 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. Qualifications Your profile We seek a detail-oriented Applied Scientist with a Master’s in Computer Science, Statistics, Applied Mathematics, Quantitative Genetics, or related fields. You combine strong technical skills, analytical insight, and a collaborative mindset. Programming: Skilled in Python, R, SQL; experienced with relational and NoSQL databases. Cloud: Familiar with AWS services and infrastructure. Analytics: Able to uncover patterns in large datasets and translate findings into actionable recommendations. Collaboration: Effective team player, able to communicate technical concepts to diverse stakeholders. Bonus: Experience with Docker/Kubernetes, machine learning frameworks (Keras, PyTorch, scikit-learn), and interest in plant breeding or agricultural innovation. Additional Information What We Offer: · A culture that celebrates belonging and collaboration, promotes professional development and strives for a work-life balance that supports the team members. Offers flexible work options to support your work and personal needs. · Full Benefit Package (Medical, Dental & Vision) that starts your first day. · 401k plan with company match, Profit Sharing & Retirement Savings Contribution. · Paid Vacation, Paid Holidays, Maternity and Paternity Leave, Education Assistance, Wellness Programs, Corporate Discounts, among other benefits. Syngenta has been ranked as a top employer by Science Journal. Learn more about our team and our mission here: https://www.youtube.com/watch?v=OVCN_51GbNI 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.

Responsibilities

The role focuses on designing, implementing, and optimizing scalable data pipelines to integrate and consolidate data from multiple sources, ensuring data quality and reliability for stakeholders. Key tasks include driving data modeling and mining, collaborating across teams, and identifying opportunities to incorporate advanced analytics and machine learning frameworks.