Data Scientist – Agriculture

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Examine historical biological field-trial data to uncover trends and evaluate the effects of formulations, application rates, mixtures, agricultural practices, and environmental factors on product efficacy.

• Assist domain specialists in comprehending product performance and recognizing analytical opportunities.

• Analyze physical chemistry, biokinetic, formulation, marketing, and environmental data to inform decisions and design laboratory, glasshouse, and field experiments.

• Advise technical managers on the design of field trials aimed at validating scientific hypotheses and model predictions.

• Collaborate with R&D IT and software developers to enhance data-model integrations and implement customized applications.

• Monitor and investigate new modeling techniques, analytical tools, and methodologies.

• Participate in digital transformation initiatives to boost the impact of data science in predictive field trials.

• Work alongside colleagues and external partners, integrating complementary capabilities into various projects and initiatives.

⛳️ Requirements

• Solid background in data science at the postgraduate level, particularly in natural sciences (e.g., biology, ecology, environmental sciences).

• Demonstrated experience with key data science, analytics, modeling, and visualization libraries in Python, including those for machine learning and deep learning.

• Scientific expertise in relevant fields such as environmental sciences or biology.

• Previous experience in developing machine-learning models pertinent to biological or crop protection outcomes.

• Proficient in data analysis and deriving insights for new understanding.

• Capable of conveying scientific and data concepts to both specialized and non-specialized audiences.

• Flexible in adapting to various business challenges and different data types/sources.

• Willingness to learn and apply a variety of analytical tools and methodologies.

• Skillful in visualizing data and crafting compelling narratives with it.

• Strong analytical problem-solving abilities and innovative thinking.

• Effective collaboration across diverse teams while managing multiple priorities in a multicultural scientific setting.

• Practical experience with generative AI approaches is a bonus.

• A CV, cover letter, and a one-page dataset exploration document are required for application.

🏝️ Benefits

• Comprehensive benefits package.

• Generous pension plan.

• Bonus scheme.

• Private medical insurance (subject to the contracting country).

• Life insurance (subject to the contracting country).

• Flexible working arrangements.

• A culture of continuous learning.

• A wide array of training options.