Use data science and ML to shape how millions of people cook at home — and actually see your models in production.

About Marley Spoon

Marley Spoon is a food-tech company on a mission to help people cook better, eat smarter, and waste less. We deliver flexible meal solutions across six countries, powered by data that touches everything from menu planning and marketing to operations and logistics.

Our Data & Digital Product teams work closely with Marketing, Operations, and Engineering to ship things that matter: better customer experiences, less waste, and a more resilient business.

The Role

We’re looking for a Lead Data Scientist, Growth & Personalization who wants to own the applied DS/ML roadmap for key growth and customer problems — not just ship a one-off model and move on.

This is a senior, hands-on role where you will:

• Set the direction for how we use data science & ML across personalization, forecasting, marketing, and retention
• Lead and mentor a small, high-impact group of Data Scientists and ML Engineers
• Stay close to the code, the models, and the decisions they drive day-to-day

If you enjoy moving between strategy, experimentation, and implementation, this will feel like home.

What you’ll work on

You’ll sit at the intersection of Data, Product, and Marketing, with a clear mandate to improve how we acquire, serve, and retain customers. You will:

• Shape the DS/ML roadmap
  • Define and evolve a practical roadmap aligned with company priorities
  • Prioritise problems based on business impact and feasibility
• Lead applied data science & ML work
  • Design and build models for:
    • Customer personalization & recommendations (meals, content, communications)
    • Forecasting for demand, supply chain, and operations
    • Marketing effectiveness (targeting, attribution, LTV, CAC payback)
    • Retention & churn prevention across the customer lifecycle
  • Own models end-to-end: problem framing, feature design, evaluation, deployment, and monitoring
• Drive experimentation
  • Partner with Product & Marketing on A/B tests, hold-outs, and other experiments
  • Set up guardrails, define success metrics, and make clear trade-offs
• Build foundations for sustainable DS/ML
  • Work with Data Engineering and Platform on MLOps best practices
  • Improve reliability, observability, and documentation of our DS/ML systems
  • Raise the bar on how we use data across the organisation

About you

You treat data science and ML as tools for solving real problems, not buzzwords. You’re comfortable with complexity, but you care most about business outcomes and maintainable systems.

We’d love to hear from you if you:

• Have 4+ years in data science / machine learning, including at least 2 years in a lead capacity
• Have owned production DS/ML systems in a product or growth context (not just PoCs)
• Are fluent in Python and SQL, and have worked with common ML libraries (e.g., scikit-learn, XGBoost; any deep learning framework is a plus)
• Are comfortable with a modern data stack (e.g., Snowflake/BigQuery, dbt, orchestration tools, dashboards)
• Have led and mentored other Data Scientists / ML Engineers, formally or informally
• Communicate clearly with both technical and non-technical stakeholders and can translate between “model metrics” and “business outcomes”
• Enjoy switching between hands-on coding, roadmap thinking, and stakeholder conversations

Nice to have (but not required):

• Experience in e-commerce, subscription, or consumer products
• Familiarity with marketing, CRM, lifecycle, or pricing analytics
• Experience working in a fast-moving scale-up environment

How we work

• Hands-on leadership – you’ll still be coding, reviewing, and designing experiments.
• Cross-functional by default – you’ll collaborate with Product, Marketing, Ops, and Engineering regularly.
• Pragmatic DS/ML – we care more about robust, explainable models that improve decisions than chasing hype.

Benefits

We believe in balance, growth, and building a workplace where people can do their best work over time. Our benefits reflect that.

Here’s what we offer:

• Hybrid setup: Work remotely with regular collaboration time in Portugal
• Generous leave: 22 vacation days + 2 extra per year of tenure (up to 6)
• Learning support: 5 paid training days annually
• Health coverage: Private insurance via Allianz
• Daily food allowance: €7.62 per worked day
• Wellbeing support: Confidential employee assistance program (24/7)

Ready to apply?

If you’d like to build DS/ML systems that are used every day — and see your work directly shape how people cook at home — we’d love to hear from you.