Agronomy Graduate

Maidstone
3 weeks ago
Create job alert

Are you looking for a field-based role where you can combine your agricultural knowledge and analytical mindset to help shape Fresh Produce supply decisions?
Agronomy Graduate Overview
The Agronomy Graduate role offers a unique opportunity to work at the intersection of crop science, data analysis, and commercial planning within the Fresh Produce sector.
You will play a critical part in helping the business forecast short and mid-term supply, ensuring the most accurate production data informs strategic decisions across a wide grower base.
The Agronomy Graduate role involves regular travel across the Midlands and fortnightly visits to Head Office in Kent, allowing some flexibility for the successful individual’s location.
This is a field-focused position (approximately 70% field, 30% office), and you will work closely with growers, agronomists, and internal stakeholders across the UK and occasionally in other EMEA regions.
Agronomy Graduate Key Responsibilities

  • Conduct weekly field visits to collect accurate crop production data from growers.
  • Monitor crop development and assess the impact of weather on short- and mid-term yields.
  • Support the analysis of production data to create accurate supply forecasts by grower, variety, treatment, and region.
  • Maintain and update seasonal production databases and forecasting tools.
  • Track forecast accuracy and support ongoing improvements in process and data quality.
  • Liaise closely with growers and internal teams including Operations, Supply Chain, and Planning.
  • Support broader forecasting strategy through collaboration across regions.
  • Contribute to the development of the region’s analytical and forecasting capabilities.
    Agronomy Graduate Key Requirements
  • A degree in Agriculture or a related field, with knowledge of data analytics and statistics
  • Experience in Horticultural or Fresh Produce crops, ideally with exposure to data analysis
  • Comfortable working in a field-based role with frequent travel to grower sites
  • Solid understanding of crop science and seasonal production cycles
  • Proficiency in Microsoft Excel, Word, and PowerPoint
  • Intermediate knowledge of statistical data analysis
  • Full UK driving licence
    This is an exciting opportunity for a proactive and detail-oriented individual to develop their career in a forward-thinking Fresh Produce business. The role offers growth potential and the chance to work at the core of a team focused on innovation, sustainability, and high-quality forecasting.
    If you are passionate about agriculture and enjoy turning data into decisions, please get in touch!
    This is a UK-based position. Applicants must have the legal right to work in the UK. Evidence of this right will be requested prior to interview, if applicable

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.