Jobs in Frankfurt, Deutschland

Help us use data and machine learning to help people cook better, eat smarter, and waste less – from the comfort of your home in Portugal, with the option to join us in our Lisbon office for collaboration days.

We’re Marley Spoon — a food‑tech company on a mission to make home cooking easy, joyful, and more sustainable. Since 2014, we’ve grown into a global meal kit platform, delivering flexible, personalised recipes to customers across six countries.

Behind every box is a network of intelligent systems, built by lean, cross‑functional teams who care deeply about customer experience, sustainability, and quality. Our Data Tribe plays a key role in making that happen—one model, one insight, one experiment at a time.

As a Data Scientist in our Data Tribe, you’ll work at the intersection of machine learning and practical business impact. You’ll collaborate with Product, Marketing, Engineering, and Operations to build models and tools that power how we personalise, plan, and continuously improve our customer experience.

This is a hands‑on role with room to learn, experiment, and grow. You’ll have real ownership across the lifecycle of your work—from framing the problem, to building and validating models, to deploying and monitoring them in collaboration with our engineering and product teams.

• Improving the way we recommend meals and content to our customers.
• Helping teams make better decisions through robust forecasting and experimentation.
• Delivering models that are used in production and demonstrably support core business outcomes.

• Design, build, and improve personalisation and recommendation models that tailor meal kits, recipes, and content to each customer’s tastes and behaviours.
• Develop and maintain forecasting and planning models that help us predict demand, optimise logistics, and reduce food waste.
• Support retention and marketing initiatives with churn prediction, CLV modelling, and campaign optimisation.
• Explore and apply newer technologies (e.g. LLMs, generative AI) where they add real value – in close partnership with product and engineering.
• Help design and analyse A/B tests and experiments, ensuring decisions are backed by solid evidence.
• Work end‑to‑end on your models: from data exploration and feature engineering through validation, deployment (with our engineering partners), and performance monitoring.
• Collaborate closely with other Data Tribe members to share knowledge, review work, and evolve our data science practices.

You enjoy making models that are useful, not just elegant, and you’re curious about the “why” behind every problem. You’re collaborative, thoughtful, and comfortable working in an international environment.

• Around 3+ years of experience in applied data science or a similar role.
• Solid knowledge of machine learning, statistics, and time‑series modelling; experience with recommender systems is a plus.
• Proficiency in Python and SQL, and hands‑on experience with common ML libraries (e.g. scikit‑learn, PyTorch, XGBoost).
• Experience working with modern data platforms (e.g. Snowflake, Looker, Airflow or similar tools).
• A sense of ownership: you care about the quality, reliability, and impact of the solutions you deliver.
• Ability to explain complex ideas in simple, clear language to non‑technical stakeholders.

• Experience in subscription, e‑commerce, or consumer products businesses.
• Previous work on personalisation, recommendations, or customer lifecycle topics.
• Exposure to LLMs or generative AI in real product use cases.
• Experience working in Agile, cross‑functional product teams.

If you don’t meet every single point but feel you could grow into this role, we’d still like to hear from you.

• This role is remote within Portugal.
• You’re welcome (but not required) to join us in our Lisbon office for collaboration days, workshops, and social activities.
• We work mainly during standard CET business hours, with flexibility to balance focused work, meetings, and life outside of work.
• We value outcomes over hours and trust people to manage their time responsibly.

• The chance to work on meaningful problems that connect directly to how people cook and reduce food waste.
• A supportive, cross‑functional environment where data, product, and engineering work closely together.
• Opportunities for learning and growth through feedback, experimentation, and exposure to different business areas.
• A culture that values impact, collaboration, and sustainable ways of working.

• Hybrid work policy (remote + office).
• 22 annual leave days +2 days extra days for every year of tenure (up to 6).
• 5 training days per year.
• Private health insurance provided by Tranquilidade.
• Food allowance of 7.62€/worked day under by Coverflex.
• 24/7 confidential employee assistance program.