Kynetec is the global leader in agricultural and animal health market insights. We have a long history of market research expertise, specialising in animal health and nutrition, crop protection, farm machinery and equipment, seed/biotech and fertilisers.

Backed by a team of more than 850 market researchers, interviewers, data analysts, marketing scientists, research operation and data visualization specialists, our number one priority is to ensure that we deliver the highest-quality insight and foresight at the right time to enable our clients to confidently make the best decisions for their business.

Across the globe, our employees are located across 28 major agriculture and animal health countries. Our coverage extends to major and niche sectors of our industry, where we regularly undertake research projects in more than 80 countries.

To strengthen our team, we are seeking a Data Scientist on a permanent contract to join our advanced analytics team. We build data and AI tools that empower decision-making in global agriculture markets.

From pricing, forecasting to churn and farmer analytics, we apply advanced machine learning in a domain that truly matters.

If you’re ready to go beyond model-building and want to create systems that are smart, scalable, and impactful this could be the role for you.

Key responsibilities:

• End-to-End Ownership: Drive the entire data science lifecycle—from problem framing, data exploration, modeling, deployment, to performance monitoring
• Collaboration & Co-Creation: Work closely with Product Managers, Engineers, and Stakeholders across geographies to shape data-driven solutions with real-world impact
• Product Analytics & Forecasting: Build models and systems that improve demand planning, pricing, and behaviour prediction
• Experimentation & Road mapping: Design, test, and iterate on ML experiments; set milestones and continuously improve
• Scalable Infrastructure: Follow best practices in MLOps and software engineering to ensure reusable and maintainable pipelines
• Automation Mindset: Build systems that automate repetitive tasks across analytics workflows (e.g. feature generation, model tracking)
• AI-Tooling: Use AI tools/frameworks (e.g. ChatGPT, GitHub Copilot, Agents) to boost productivity and support faster experimentation
• Insight Communication: Translate complex findings into actionable business recommendations for technical and non-technical audiences

Skills required:

• Degree in computer science, Statistics, Engineering, Mathematics, Bioinformatics or similar
• Preferably 2-4 years’ experience in data science
• Professional level English - verbal and written
• Strong background in applied machine learning and data modeling (e.g. regression, classification, tree-based models, clustering)
• Solid grasp of mathematics, statistics, and applied analytics in real-world settings
• Experience with Python (pandas, scikit-learn, etc.) and SQL.
• Familiarity with distributed computing frameworks (e.g. Spark, Dask) is a plus.
• Practical knowledge of ML Ops principles: model deployment, testing, monitoring
• Cloud experience (Azure Databricks, AWS, or GCP) preferred
• Self-driven and adaptable mindset, able to work independently and across time zones
• Excellent communication and presentation skills

What you can expect:

• Work with a modern AI-native stack (e.g. MLflow, Azure ML, Copilot, vector stores)
• Exposure to international teams and cross-functional collaboration
• Structured onboarding with clear milestones and feedback
• Continuous learning & access to global resources