Data Science Graduate Management Trainee at Greenspoon

Greenspoon is hiring a Data Science Graduate Management Trainee who will work within product teams, using data, models, and tools to help Operations, Commercial, Marketing, and Finance make smarter, faster decisions. Your day-to-day involves analyzing customer and sales data, building reliable data pipelines, creating internal tools, automating tasks, forecasting demand, and designing experiments. If you have a quantitative degree and are excited by real-world data challenges, read on.

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Greenspoon is Kenya's fastest growing online supermarket, delivering thousands of delicious, healthy, and fresh groceries directly to our customers' homes every day. We are building East Africa's largest online supermarket with exceptional service and quality at an every day price. We pride ourselves on offering the widest range of organic fruits and vegetables, freshly baked breads, quality meats, and much more! We delight you with everything that you love and everything that you need.

We deeply care about our customers, suppliers, employees, and the environment. We believe this is the reason we have grown 15x over the last four years. We embody our values, honesty, quality, and impact, every day. As a certified B Corp, we hold the highest global mark of sustainability, placing us in the same league as brands like Patagonia, Ben & Jerry's, and BrewDog. We are a sustainable enterprise that is also profitable. We are optimistic about the future and have strong confidence in our abilities. Our team is young, extremely talented, and driven to make an impact.

Role: Graduate Management Trainee Data Science

Are you ready to kickstart your career in 2026? Do you love turning messy data into clear answers, and answers into tools that people actually use? Greenspoon is looking for a Graduate Management Trainee to join our Data Science team. You will sit inside our product teams and work shoulder to shoulder with Operations, Commercial, Marketing, and Finance, helping them make better decisions and run faster through data, models, and lightweight tools.

Given the phase of the business, start up to scale up, the questions landing on your desk every day are real and varied. Why did basket size drop on Tuesdays? How many crates of strawberries should we order next week? Which customers are about to churn? Where is the bottleneck in our picking process? You will get to work on all of it.

What You Will Do

You will rotate across the business and embed inside different product teams, owning end-to-end work that spans:

• Analysis: digging into customer, sales, supply chain, and operational data to surface insights that change decisions
• Data engineering: building and maintaining clean, reliable data pipelines and tables that the rest of the company can trust
• Tool building: creating simple, useful internal tools using Google AppScript, Sheets, and our existing stack so that teams can self serve
• Automation: removing repetitive manual work through scripts, scheduled jobs, and integrations between our systems
• Forecasting: building demand, sales, and operational forecasts that drive purchasing, staffing, and planning
• Experimentation: designing and analysing A/B tests across pricing, promotions, app features, and operational changes
• Dashboarding and reporting: building clear, decision oriented dashboards that managers actually use, not vanity reports

You will present your work to leadership, defend your assumptions, and ship things that the business depends on.

Qualifications

• Excellent academic achievement
• Bachelor's or Master's degree in computer science, statistics, mathematics, engineering, economics, or a similar quantitative field
• 0–2 years work experience
• Working knowledge of SQL and at least one programming language, ideally Python
• Desirable experience with GitHub and analytics engineering tools such as dbt
• Desirable experience in deploying ML models in production environments
• Comfortable in Google Sheets and a plus if you have already touched Google AppScript or any scripting for automation
• Exposure to forecasting, machine learning, or experimentation is a plus, but not required
• Ready to work in a fast-paced environment where priorities shift week to week

Candidates Should Possess the Following Traits

• Analytical mindset: you enjoy breaking down complex problems and following the data wherever it leads
• Curiosity: you ask why, and then you ask why again, until you actually understand what is going on
• Builder mentality: you would rather ship a rough working tool today than a perfect one in three months
• Strong communicator: you can explain a model or a finding to a warehouse supervisor, a commercial lead, and a CEO, all in language that lands
• Willingness to speak up: you challenge weak assumptions, push back on bad data, and raise issues early
• Discipline and consistency: your numbers are right, your code is reviewable, and your work is reproducible
• Ownership: you treat the problem as yours, not as a ticket that gets handed off
• Hands on attitude: you are happy to spend a morning in the warehouse or on a delivery route to understand the data you are working with

What You Will Learn

• How to apply data science in a real, fast moving commercial environment, not in a textbook
• The full data stack we use day to day, from SQL and Python to Google AppScript and BI tools - powered by a company-wide Claude Code program
• Forecasting methods, experimentation design, and basic machine learning applied to retail and supply chain problems
• How to work inside product teams, scope problems with stakeholders, and turn ambiguity into clear deliverables
• Strong commercial and operational intuition across grocery retail, e-commerce, and logistics

We will provide you with training and on the job coaching. You will have a personal development budget that you can use to pursue further courses, certifications, or relevant books. The contract is initially for one year, and if successful we will offer you a permanent role in the team that best matches your strengths, with a clear path to grow into senior data, analytics, or product roles across the business.

Apply for this vacancy

Deadline: Sunday, May 31, 2026

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