Summer Intern - Predicting Kiwifruit Conditioning Performance

Zespri Group Limited; Mount Maunganui; On-site; NZD 67,000 - 100,000; Full time

Benefits offered by this job

Free onsite parking

Full project exposure

Job summary

Zespri invites a curious and analytical Summer Intern to join our Conditioning Team in Mount Maunganui. You’ll help develop a data-driven tool that predicts kiwifruit softening by integrating time, temperature and ethylene exposure, combining data science with postharvest research.

Working alongside our team, you’ll analyse historical data, review literature, build predictive models and deliver a practical decision-support tool with clear recommendations for conditioning decisions across the

Qualifications

• Currently pursuing or recently completed a science/technology/horticulture or business degree at NZQA level 6-10
• Programming capability in Python or R and interest in postharvest science or data-driven decision tools

Responsibilities

• Review scientific literature and historical conditioning data to identify key drivers of fruit firmness.
• Analyse datasets relating to time, temperature, ethylene exposure and fruit softening.
• Develop a unified conditioning metric combining multiple variables.
• Build and validate models to predict firmness.
• Test and refine models with historical and current-season data.
• Deliver a practical decision-support tool for operational use.
• Present findings, recommendations and future opportunities for development.

Skills

Python or R

Analytical thinking

Data analysis

Education

Undergraduate or postgraduate degree related to science/tech/horticulture or business

Tools

Python

R

Job description

Summer Intern - Predicting Kiwifruit Conditioning Performance

Zespri is more than simply the world's single-largest marketer of kiwifruit. We like to think of ourselves as fruit on a mission and as rebels with a cause: to help people, communities and the environment around the world thrive through the goodness of kiwifruit. We are proudly the world's largest marketer of kiwifruit, selling kiwifruit in more than 50 countries. We work with around 2,800 New Zealand and 1,500 international growers and post-harvest companies to source the best-quality Zespri Kiwifruit which we supply through our distribution partners to wholesale and retail customers. We are one of New Zealand's best-known international brands, dedicated to creating sustainable long-term value for growers.

He aha te mahi? What's the role?

We're looking for a curious and analytical Summer Intern to join our Conditioning Team and help develop a data-driven tool that predicts how kiwifruit softens during conditioning. This is a unique opportunity to combine data science, modelling, and postharvest research to help develop a predictive conditioning metric that integrates time, temperature, and ethylene exposure to better understand and predict fruit softening.

Today, conditioning decisions often rely on experience and trial-and-error. This project aims to create a more quantitative and repeatable approach that helps achieve market-specific firmness targets and improve fruit quality outcomes. Working alongside our Conditioning Team, you'll analyse historical data, review scientific literature, build predictive models, and develop a practical decision-support tool that can be used to support conditioning decisions across the business.

Key activities include:

• Reviewing scientific literature and historical conditioning data to understand the key drivers of fruit firmness.
• Analysing datasets relating to time, temperature, ethylene exposure, and fruit softening.
• Developing a unified conditioning metric that combines the effects of these variables.
• Building and validating models that predict firmness outcomes.
• Testing and refining the model using historical and current-season data.
• Developing a practical decision-support tool for operational use.
• Presenting findings, recommendations, and future opportunities for development.

By the end of the internship, you'll deliver a validated predictive conditioning metric, a practical decision-support tool, and recommendations that help move conditioning decisions towards a more data-driven approach.

Program dates: 23 November 2026 – 12 February 2027. Please note: You must be available for the full duration of the internship.

Ko wai koe? Who are you?

The ideal candidate will be naturally curious, highly analytical, and excited by the opportunity to turn complex data into practical business insights. You'll enjoy problem-solving, working with data, building statistical, mathematical or data-driven models, applying quantitative thinking to real-world challenges. You’ll have programming capability in Python or R and interest in postharvest science, fruit physiology or operational decision-support tools.

To be eligible to apply you need to meet the following selection criteria:

• Studying, or recently completed, an undergraduate or postgraduate degree or qualification at NZQA level 6-10. If study has been completed, your final semester should be less than 12 months ago.
• Studying or has studied science, technology, engineering,data science or horticulture designor business studies at a New Zealand tertiary education institute.
• Legallypermittedto work in New Zealand.

This rolewill be based in the beautiful Bay of Plenty, a great place to spend the summer. Beaches, waterfalls and the Kaimai ranges all close by for summer day adventures! You will work out of our state of the art corporate office in central Mount Maunganui, have access to daily kiwifruit, free onsite parking, and a flexible work ethos. Please note, you will need to manage your own accommodation for the duration of the internship.

At Zespri, we understand the importance of diverse perspectives and experiences, and a fair hiring process is the first step to getting there. We want to attract a diverse range of people and encourage everyone from all backgrounds and walks of life to apply. Please let us know if you need any assistance or reasonable adjustments to take part in the recruitment and selection process by reaching out to our Talent Acquisition team via email at [e-mail].