At Marley Spoon, we create flexible, high-quality food experiences for customers around the world. Behind every delivery is a set of data-driven systems that helps us understand customer preferences, plan more efficiently and reduce food waste.

We are looking for a Data Scientist to help us turn that data into practical machine learning solutions that improve personalization, forecasting and decision-making across our business.

This is a hybrid role based in Portugal, with regular collaboration from our Lisbon office alongside flexible remote work.

The role in a nutshell

Joining our Data Tribe, you will develop and deploy models that connect directly to meaningful customer and business outcomes.

Your work could help customers discover meals they are more likely to enjoy, enable our teams to forecast demand more accurately, strengthen retention initiatives or support better operational planning.

You will work closely with Product, Engineering, Marketing and Operations, taking ownership from initial problem framing and experimentation through to deployment, monitoring and continuous improvement.

What you’ll bring

You are an applied Data Scientist who enjoys solving real-world problems, not simply building models in isolation. You care about how your work performs in production, how clearly it can be understood and whether it ultimately changes a decision or improves an outcome.

You will also bring:

• Around 3+ years of experience in applied data science or a closely related role.

• Strong foundations in machine learning, statistics and time-series modelling, with recommender-system experience considered a plus.

• Strong proficiency in Python and SQL, with hands-on experience using libraries such as scikit-learn, PyTorch and XGBoost.

• Experience working with modern data platforms and tools such as Snowflake, Looker and Airflow, or comparable technologies.

• Experience taking models beyond experimentation and contributing to reliable, maintainable production solutions.

• The ability to explain complex technical concepts clearly to non-technical stakeholders.

• An ownership mindset and a strong focus on practical, measurable impact.

Experience in subscription, e-commerce or consumer-product environments would be valuable, as would prior work in personalization, recommendations, customer lifecycle modelling or product applications of generative AI.

Experience working in Agile, cross-functional product teams would also be beneficial.

If you do not meet every requirement but believe you could grow into the role, we would still be pleased to hear from you.

Joining us, you will…

• Build and improve recommendation and personalization models that tailor meals, recipes and content to customer preferences and behaviour.

• Develop time-series forecasting and planning models that improve demand prediction, logistics decisions and food waste reduction.

• Support customer retention and marketing initiatives through churn prediction, customer lifetime value modelling and campaign optimization.

• Design and analyse A/B tests and other experiments using robust statistical methods, including effect sizing and uncertainty.

• Explore newer approaches, including large language models and generative AI, when they provide a practical solution to a real customer or business problem.

• Take models from exploration and feature engineering through validation, deployment and production monitoring, working closely with Engineering.

• Clearly document model assumptions, performance and limitations so teams can confidently use the outputs.

• Contribute to code reviews, knowledge sharing and the continued development of strong Data Science practices across the tribe.

What success could look like

Within your first 6–12 months, you will have shipped at least one model into production and demonstrated how it supports a meaningful business or customer outcome.

You may have improved recommendation quality through measurable iteration, delivered forecasting work that supports clearer operational planning or helped a team make a stronger decision through rigorous experimentation.

Just as importantly, you will have become a trusted cross-functional partner, known for bringing clarity, technical rigour and ownership to complex problems.

How we work

This is a hybrid role based in Portugal, combining regular in-person collaboration at our Lisbon office with flexible remote work.

We generally work within CET business hours, with flexibility. We focus on outcomes and trust people to manage their time responsibly.

What’s in it for you

• Meaningful machine learning problems connected to how people cook, shop and discover food.

• The opportunity to build solutions that improve customer experiences and help reduce food waste.

• Close collaboration across Data, Product, Engineering, Marketing and Operations.

• Learning and growth through experimentation, feedback and exposure to different areas of the business.

• A culture that values impact, technical craft and sustainable ways of working.

Benefits:

• 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.