Data Scientist

Описание вакансии

At Too Good To Go, we have an ambitious goal: to inspire and empower everyone to fight food waste together.

40% of all food produced in the world is wasted. And that has a huge impact on the health of our planet, with 10% of greenhouse gas emissions coming from food waste.

We’re more than an app: we are a certified B Corporation with a mission to empower everyone to take action against food waste, so alongside our marketplace app, we create educational tools, explore new business solutions - such as our Retail Technologies offering, and influence legislation to help reduce food waste.

We’re growing fast: Our community of 133 million registered users and 261,000 active partners across 21 countries, have together already prevented 517+ million meals from going to waste - avoiding over 1.397.000 tonnes of CO2e!

Your mission

We are looking for a Data Scientist to join our Product Analytics and Center of Excellence team at Too Good To Go.

In this role, you will help build and scale data science capabilities across product and business domains, enabling smarter, more automated, and more impactful decision-making.

As a marketplace, many of our most critical challenges revolve around supply-demand dynamics, user behavior, and marketplace efficiency. You will work on problems such as personalisation, optimisation, and forecasting, helping us move from reactive analysis to proactive, model-driven systems.

You will work as part of the Center of Excellence, partnering closely with Product, Analytics, and business teams through high-impact, project-based collaborations.

Your role

• Partner with Product and business leaders to identify high-impact opportunities where data science can drive step-change improvements
• Develop and deploy machine learning models and statistical methods to solve problems such as: Personalisation and recommendation systems, Marketplace optimisation (e.g. ranking, matching, supply-demand balance) and Demand and supply forecasting.
• Translate ambiguous business problems into scalable models, algorithms, and data products
• Design and contribute to experimentation and measurement frameworks to evaluate impact
• Collaborate closely with Product Analysts, ML Engineers, and stakeholders within the Product Analytics and Center of Excellence, working in an embedded, project-based model
• Take end-to-end ownership, from problem framing to model development and impact evaluation
• Contribute to building data science best practices, tools, and standards across the company

Requirements

• Master’s degree or PhD in Data Science, Statistics, Machine Learning, Econometrics, or a related field
• Strong experience applying machine learning and statistical modeling to product or business problems
• Experience in at least one of the following areas: Personalisation / recommendation systems, Marketplace or optimisation problems, Forecasting (time series or causal)
• Strong programming skills in Python and solid proficiency in SQL
• Experience with experimentation (A/B testing) and impact measurement
• Ability to operate in ambiguous problem spaces and translate them into structured solutions
• Strong communication skills — able to influence product and business stakeholders
• High ownership and comfort working in a fast-paced, evolving environment
• Fluent in English, with excellent written and verbal communication skills.

Our values

• We win together: Food waste is a big beast to fight. We believe in a #oneteam.
• We raise the bar: We always push for more. We work smart, smash barriers and elevate one another.
• We keep it simple: Our ambitions are bold but our solutions are simple.
• We build a legacy: We’re proud of the change we’re driving.
• We care: We always look out for each other. Caring is also about the way we do business. We do the right thing.

What We Have To Offer

• An opportunity to work in a global social-impact company and certified B Corporation! where you can see a real and tangible impact in your role.
• To be an integral part of our Data & Analytics team. We are eager for you to make an impact and contribute to the role of analytics across key decisions and our solution processes. Your insights are valuable, and we are here to listen.
• Work-life balance is important to us! Focus on the job to be done, not the hours spent, there is no need for overtime.
• We trust in our employees and encourage an autonomous environment that provides several opportunities for employees to contribute, develop and take ownership of their work in a way that works for them.
• To be part of an international company, with over 1,300+ colleagues across 19 countries that are on the same important mission.
• An informal environment, working alongside 170+ passionate people within Tech & Product
• We celebrate our differences and our successes and have a strong values-driven team culture.
• We work in a hybrid set-up and value in office work weekly.
• We may be able to support you with a working visa in Copenhagen, please be prepared to discuss this topic further as your first stage interview.

How to apply

• We take recruitment very seriously, so please carefully read everything we have written above. Please also check our website and international media in order to get a good overview of Too Good To Go.
• Submit your CV in English.
• Please note that we only accept applications coming through our platform. No CV will be accepted by email or LinkedIn direct messaging.

Job Ref: #LI-CT1

A Movement for Everyone

We want to inspire and empower everyone to fight food waste together. With that mission, it’s only natural that we want to build a diverse and inclusive team of highly capable individuals who are passionate about doing things in a better way. We strongly believe we all excel and are more creative when we’re allowed to be ourselves, and we’re committed to a culture where all of us belong.

We are an equal opportunity employer and all employment is decided on the basis of qualifications, merit and business need. If you need reasonable accommodation at any point in the application or interview process, please let us know.