Data Scientist

Join Syngenta Group, a leader in agricultural innovation where technology meets purpose. As digital pioneers in AgTech, we're integrating AI across our value chain from smart breeding to precision agriculture. Our global team of 56,000 professionals is transforming sustainable farming worldwide. At Syngenta IT & Digital, your expertise will directly impact food security and shape the future of agriculture through cutting-edge technology.

Website address - https://www.syngentagroup.com/

Role purpose

• Support the development and deployment of AI, ML, and predictive analytics models in collaboration with senior data scientists
• Work as part of a Data Science team to integrate diverse data sources and enable data-driven decision-making across functional boundaries
• Contribute to innovative analytical solutions that help enable users and decision makers solve business problems and drive measurable outcomes

Accountabilities

• Assist in building predictive models and analytics capabilities under guidance of senior team members
• Perform data analysis and exploratory data analysis (EDA) to develop fact-based insights and recommendations
• Support the integration of traditional (internal) and nontraditional (external) data sources into analytical workflows
• Contribute to data mining initiatives to extract insights from structured and unstructured data
• Conduct data cleaning, preprocessing, and validation to ensure data completeness and quality
• Work with unstructured datasets to identify patterns and emerging trends
• Document data sources, methodologies, and analytical processes
• Maintain data pipelines and support data integration activities
• Work with cross-functional teams (key users, engineers, domain experts) to understand problem statements and requirements
• Translate analytical findings into clear, actionable insights for non-technical audiences
• Participate in agile team ceremonies and contribute to sprint planning and execution
• Engage with business users to understand their needs and validate analytical approaches
• Participate in team knowledge-sharing sessions and training programs
• Learn industry best practices for statistical programming, modeling, and data visualization
• Build domain knowledge in relevant business areas (Marketing, Sales, Supply Chain, R&D)

Critical success factors & key challenges

• Clear Communication: Effectively convey analytical scope, limitations, and risks to business
• Data Completeness: Ensure all essential information is captured and validated for analysis
• Business Applicability: Deliver insights and models that directly address business goals and requirements
• User Engagement: Build relationships with business users and demonstrate value through data-driven solutions
• Curate Documentation: Keep and archive documentation following the establish good practices

Knowledge, experience, education & capabilities

Critical knowledge:

• Understanding of fundamental data science algorithms including data cleaning, clustering, and pattern recognition
• Basic statistical analysis skills with ability to apply appropriate techniques to business problems
• Ability to translate business questions into analytical approaches with guidance
• Foundational programming skills in Python for data analysis and statistical modeling
• Understanding of data structures, algorithms, and basic software development principles
• Familiarity with data visualization techniques to communicate insights effectively

Critical experience:

• Demonstrated experience with data analysis through internships, academic projects, capstone projects, or entry-level roles
• Hands-on experience with Python and Python Libraries (pandas, numpy, matplotlib/seaborn)
• Exposure to SQL and relational databases for data extraction and manipulation
• Basic understanding of statistical methods and machine learning concepts
• Experience working in team environments (academic group projects, internships, or collaborative work)

Bachelor's degree in Computer Science, Mathematics, Statistics, Data Science or related quantitative fields

Note: 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, gender identity, marital or veteran status, disability, or any other legally protected status.

Follow us on: LinkedIn

LI page - https://www.linkedin.com/company/syngentagroup/posts/?feedView=all