Data Scientist

Company Description

Syngenta Seeds is one of the world’s largest developers and producers of seed for farmers, commercial growers, retailers and small seed companies. Syngenta seeds improve the quality and yields of crops. High-quality seeds ensure better and more productive crops, which is why farmers invest in them. Advanced seeds help mitigate risks such as disease and drought and allow farmers to grow food using less land, less water and fewer inputs.

Syngenta Seeds brings farmers more vigorous, stronger, resistant plants, including innovative hybrid varieties and biotech crops that can thrive even in challenging growing conditions. Syngenta Seeds is headquartered in the United States.

Job Description

Join our dynamic and innovative global team as a Data Scientist, where you will have the opportunity to empower farmers with cutting-edge, data-driven solutions. As a key player in our multidisciplinary team, you will work closely with Data Scientists, Data Engineers, and MLOps specialists to design and deploy state-of-the-art ML systems. From discovery to deployment, you will drive the roadmap, design, automation, and streamlining of our Machine Learning operations, bringing your expertise in Data Science to solve complex problems and ensuring the implementation of best practices.

We all have a critical role to play and add value. Here is how this role will help:

• Design, develop, experiment, and evaluate AI/ML models to address Seeds Development challenges
• Build and advance our ML platform in collaboration with talented teams of specialists
• Play a key role in deploying new ML capabilities and services for our product teams
• Become a subject-matter expert in ML design and implementation, promoting best practices
• Contribute to a positive and collaborative team culture, focused on technical excellence and innovation.

Qualifications

At our company, we prioritize our people and seek professionals who are passionate, collaborative, and excel in their execution. Leaders are expected to communicate effectively, develop teams and lead by example. Our industry and our function are changing rapidly, so we seek team members with a strong desire to develop themselves. You will be a great fit if you have:

• A Ph.D. or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Engineering, or a related quantitative field, with at least 10 years of experience in Deep Learning, Machine Learning, programming, data modeling, evaluation, probability, and high-dimensional datasets
• Experience with cloud computing platforms such as AWS, GCP, or Azure
• Experience with MLFlow, Kubeflow, Sagemaker, Vertex AI, or equivalent
• Experience with machine learning frameworks such as Tensorflow, Pytorch, or Keras
• Proficiency in coding (Python, Java, C#, C/C++) and scripting (Python, R, Matlab)
• In-depth knowledge of feature stores, graph databases, SQL, NoSQL, data lakes, and other data storage technologies
• Expertise in data visualization tools such as Qlik, Spotfire, or Power BI
• Excellent written and verbal communication skills
• A strong ability to collaborate effectively with technical resources in a fast-paced environment
• A problem-solving mindset with the ability to rapidly deliver innovative solutions
• Experience working in cross-functional Agile engineering teams
• Strong overall software development approach. You deliver clean, well-tested code.

Additional Information

We offer a position which contributes to valuable and impactful work in a stimulating and international environment:

• Flexible working arrangements and environment with an open culture and diverse workforce
• Learning culture (Together we Grow) and wide range of training options
• You will profit from an onsite doctor, gym, canteen, and other benefits

Interested? We look forward to receiving your online application.

Please be aware that the job title may differ from the position title.

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

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