Data Scientist

Marley Spoon
Lisbon, PortugalData Scientist$85k–$135kPosted Jul 29, 2026

<p><span>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.</span></p><p><span>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.</span></p><p><span>This is a hybrid role based in Portugal, with regular collaboration from our Lisbon office alongside flexible remote work.</span></p><h2><span>The role in a nutshell</span></h2><p><span>Joining our Data Tribe, you will develop and deploy models that connect directly to meaningful customer and business outcomes.</span></p><p><span>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.</span></p><p><span>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.</span></p><h2><span>What you’ll bring</span></h2><p><span>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.</span></p><p><span>You will also bring:</span></p><ul><li><p><span>Around 3+ years of experience in applied data science or a closely related role.</span></p></li><li><p><span>Strong foundations in machine learning, statistics and time-series modelling, with recommender-system experience considered a plus.</span></p></li><li><p><span>Strong proficiency in Python and SQL, with hands-on experience using libraries such as scikit-learn, PyTorch and XGBoost.</span></p></li><li><p><span>Experience working with modern data platforms and tools such as Snowflake, Looker and Airflow, or comparable technologies.</span></p></li><li><p><span>Experience taking models beyond experimentation and contributing to reliable, maintainable production solutions.</span></p></li><li><p><span>The ability to explain complex technical concepts clearly to non-technical stakeholders.</span></p></li><li><p><span>An ownership mindset and a strong focus on practical, measurable impact.</span></p></li></ul><p><span>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.</span></p><p><span>Experience working in Agile, cross-functional product teams would also be beneficial.</span></p><p><span>If you do not meet every requirement but believe you could grow into the role, we would still be pleased to hear from you.</span></p><h2><span>Joining us, you will…</span></h2><ul><li><p><span>Build and improve recommendation and personalization models that tailor meals, recipes and content to customer preferences and behaviour.</span></p></li><li><p><span>Develop time-series forecasting and planning models that improve demand prediction, logistics decisions and food waste reduction.</span></p></li><li><p><span>Support customer retention and marketing initiatives through churn prediction, customer lifetime value modelling and campaign optimization.</span></p></li><li><p><span>Design and analyse A/B tests and other experiments using robust statistical methods, including effect sizing and uncertainty.</span></p></li><li><p><span>Explore newer approaches, including large language models and generative AI, when they provide a practical solution to a real customer or business problem.</span></p></li><li><p><span>Take models from exploration and feature engineering through validation, deployment and production monitoring, working closely with Engineering.</span></p></li><li><p><span>Clearly document model assumptions, performance and limitations so teams can confidently use the outputs.</span></p></li><li><p><span>Contribute to code reviews, knowledge sharing and the continued development of strong Data Science practices across the tribe.</span></p></li></ul><h2><span>What success could look like</span></h2><p><span>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.</span></p><p><span>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.</span></p><p><span>Just as importantly, you will have become a trusted cross-functional partner, known for bringing clarity, technical rigour and ownership to complex problems.</span></p><h2><span>How we work</span></h2><p><span>This is a hybrid role based in Portugal, combining regular in-person collaboration at our Lisbon office with flexible remote work.</span></p><p><span>We generally work within CET business hours, with flexibility. We focus on outcomes and trust people to manage their time responsibly.</span></p><h2><span>What’s in it for you</span></h2><ul><li><p><span>Meaningful machine learning problems connected to how people cook, shop and discover food.</span></p></li><li><p><span>The opportunity to build solutions that improve customer experiences and help reduce food waste.</span></p></li><li><p><span>Close collaboration across Data, Product, Engineering, Marketing and Operations.</span></p></li><li><p><span>Learning and growth through experimentation, feedback and exposure to different areas of the business.</span></p></li><li><p><span>A culture that values impact, technical craft and sustainable ways of working.</span></p></li></ul><h4>Benefits:</h4><ul><li><p>Hybrid work policy (remote + office).</p></li><li><p>22 annual leave days +2 days extra days for every year of tenure (up to 6).</p></li><li><p>5 training days per year.</p></li><li><p>Private health insurance provided by Tranquilidade.</p></li><li><p>Food allowance of 7.62€/worked day under by Coverflex.</p></li><li><p>24/7 confidential employee assistance program.</p></li></ul>

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