About the Role
Join our Data Tribe to design, build, and deploy machine learning models that power intelligent systems across all brands and markets. You’ll own the journey from concept to production—partnering with Product, Engineering, Marketing, and Operations—to deliver data-driven solutions with real business impact in a fast-moving food-tech environment.
What You’ll Do
Deliver data science solutions
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Develop, train, and optimize models for:
- Recommender systems that personalize customer experiences
- Supply/demand forecasting and resource optimization
- Marketing efficiency (ROI, attribution)
- CLV and churn prediction for retention/reactivation
- Customer segmentation for personalization, pricing, and targeting
- Own the end-to-end lifecycle: development, validation, deployment, monitoring, and retraining.
Integrate modern AI
- Evaluate and apply emerging AI technologies—including LLMs and generative AI—to enhance internal processes and customer interactions.
Experimentation & decision support
- Design, run, and analyze A/B and multivariate tests.
- Champion a rigorous, scientific approach to decision-making.
Cross-functional collaboration
- Partner with Product, Engineering, Marketing, and Operations to solve real-world problems.
- Translate complex model results into clear, actionable insights for non-technical stakeholders.
MLOps & best practices
- Apply MLOps principles to ensure scalable, reliable, and maintainable deployments
- Collaborate on orchestration, monitoring, and retraining pipelines.
Data & AI literacy
- Advocate for responsible, data-first decision-making.
- Share best practices and mentor junior data scientists.
Your Profile
Experience
- 5+ years in data science with a track record of shipping ML models to production and delivering measurable business outcomes.
Technical proficiency
- Strong foundation in ML, statistical modeling, NLP, time-series forecasting, and recommender systems.
- Proficient in Python and SQL; hands-on with scikit-learn, XGBoost, PyTorch (or similar).
- Experience with data warehouses (e.g., Snowflake), BI tools (e.g., Looker), and model orchestration/deployment platforms.
Business orientation
- Passion for solving business problems with data and proving impact through metrics.
- Ability to turn technical work into practical recommendations.
Collaboration & communication
- Excellent cross-functional communication; influence decisions with data.
- Comfortable in Agile, iterative environments.
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 Allianz.
- Food allowance of 7.62€/worked day.
- 24/7 confidential employee assistance program.