Applied Genetics Scientist - Pipeline Data Science

Summary

Syngenta is a leading developer and producer of seeds and agricultural innovations focused on helping farmers grow more food with fewer resources. The Applied Scientist - Pipeline Data Science will build scalable data pipelines, improve data quality, and develop advanced data modeling and mining processes to support plant breeding. The role also collaborates across teams and advances predictive analytics, machine learning, and genomic prediction methods.

Responsibilities

• **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

Skills

• Master's in Computer Science, Statistics, Applied Mathematics, Quantitative Genetics, or related fields
• Skilled in Python, R, SQL
• Experienced with relational and NoSQL databases
• Familiar with AWS services and infrastructure
• Able to uncover patterns in large datasets and translate findings into actionable recommendations
• Effective team player, able to communicate technical concepts to diverse stakeholders
• Candidates must reside in and be permanently authorized to work in the United States without current or future employer sponsorship
• Experience with Docker/Kubernetes
• Machine learning frameworks (Keras, PyTorch, scikit-learn)
• Interest in plant breeding or agricultural innovation

Qualifications

Must Haves

• Master's in Computer Science, Statistics, Applied Mathematics, Quantitative Genetics, or related fields
• Skilled in Python, R, SQL
• Experienced with relational and NoSQL databases
• Familiar with AWS services and infrastructure
• Able to uncover patterns in large datasets and translate findings into actionable recommendations
• Effective team player, able to communicate technical concepts to diverse stakeholders
• Candidates must reside in and be permanently authorized to work in the United States without current or future employer sponsorship

Nice to Haves

• Experience with Docker/Kubernetes
• Machine learning frameworks (Keras, PyTorch, scikit-learn)
• Interest in plant breeding or agricultural innovation

Benefits

• 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.