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Machine Learning Scientist

Job in Greensboro, Guilford County, North Carolina, 27497, USA
Listing for: Syngenta AG
Full Time position
Listed on 2026-02-28
Job specializations:
  • Research/Development
    Data Scientist
  • IT/Tech
    Data Scientist, Data Analyst, Machine Learning/ ML Engineer, AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 110000 USD Yearly USD 80000.00 110000.00 YEAR
Job Description & How to Apply Below

Job Description

About the role

Position:
Machine Learning Scientist

Location:
We could consider candidates based at additional locations within Europe

Application process:
Carefully read instructions in  Additional Information  section

We have an exciting opportunity for a Machine Learning Scientist to join our Digital Biology Group in Crop Protection Research and Development. Within this role you will work on Syngenta biological data to uncover patterns and deliver new data-driven insights for active ingredient development across R&D functions. You will be asked to analyse and interpret the outcome of scientific experiments with your analytical skills as well as machine learning approaches.

Your work will bring forward our understanding of biological performance in crop protection and guide design, optimization and development of novel crop protection solutions. Key responsibilities will include:

  • Using exploratory analytical approaches across a range of biological lab, glasshouse & field trial data to identify the key factors impacting on performance on active ingredients.
  • Interacting with domain experts to understand scientific questions, our scientific protocols and identify analytics opportunities to drive business value.
  • Contributing to strategic business initiatives across Crop Protection data to support decision making and collaborating to design laboratory, glasshouse and field trials.
  • Collaborating and influencing the design of Research Biology capabilities to support predictive modelling activities.
  • Working with R&D IT and software developers to improve predictive model deployment applications tailored on stakeholder needs.
  • Monitoring and exploring new modelling approaches, analytical tools and methodologies.
  • Engaging with high-priority digital transformation projects to understand opportunities to accelerate the impact of data science for predictive biology studies.
  • Working with colleagues and external collaborators understanding their complementary capabilities and integrating them into projects and initiatives.
Qualifications

What we are looking for

  • Strong foundations in data science at postgraduate level with some experience in natural sciences (e.g. biology, ecology, environmental sciences).
  • Extensive experience in the use of the main data-science,
    -analytics, modelling and visualization Python libraries (i.e Pandas/Polars, Sci Py, Mat Plot Lib ).
  • Scientific domain knowledge in related fields such as biology or environmental sciences.
  • Prior experience in developing machine-learning models relevant to biological outcomes.
  • Knowledge of data analysis and extracting data insights and new understanding, while communicating scientific and data concepts to specialist and non-specialist audiences.
  • Adaptability to different business challenges and data types / sources and to learn and utilize a range of different analytical tools and methodologies.
  • Ability to visualize and story-tell with data to communicate results to shareholders with different levels of technical proficiency.
  • Analytical problem-solving skills with innovative thinking, while effectively collaborating across diverse teams and managing multiple priorities in a multicultural scientific environment.
Additional Information

Our site

We will consider candidates based at additional locations within Europe. You may be required to travel to international R&D locations and to work with collaborators globally.

Application process

Due to exceptionally high interest in this position,
we will only consider applications that include: (1) a CV, (2) a cover letter explaining your motivation and suitability for the role, and (3) a one-page document in which you tell us how (with which tools and algorithms, following which strategy) you would start exploring a 100MB CSV dataset of efficacy field trial results for a novel crop protection product including assessments for multiple crop types, trial sites and weather conditions.

Please upload your CV, your cover letter and the one-page document in separate files named “CV_###”, “_###”, and “Answer_###”, replacing ‘###’ with your family name.

What we offer

  • Extensive benefits package including a generous pension…
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