Marley Spoon is the new way to cook. We bring delightful, market fresh and easy cooking back to the people while building a sustainable supply chain for a waste-free world. We’re a well-funded and publicly listed company.

We operate across 3 continents and in 8 countries with over +1500 employees worldwide. Being passionate foodies, we are using technology to reinvent the global food supply chain to reduce food waste. In the end, it’s simple: We started Marley Spoon because we love cooking! We now have an exciting opportunity to bring a Data Scientist on board our team, working across all brands and territories. This is a once-in-a-lifetime opportunity to be part of the food revolution and join our food-tech start-up as we take our growth to the next level.

As a part of the team, you’ll be responsible for:

• Building a range of analytical models (Prescriptive, Predictive, Diagnostic, Descriptive)
• Building predictive and segmentation models (e.g. RFM segmentation, churn prediction, sentimental analysis, recommendation engines, next best offer, propensity scoring models, etc.) making use of relevant data from multiple data sources
• Deploying, maintaining and improving the models using various types of algorithms and techniques
• Mine data from multiple sources and to build/enhance stored procedures/functions
• Providing deep-dive analytical support for the business

Requirements

• MSc or Ph.D. in a quantitative discipline: Machine Learning, Computer Science, Statistics, Applied Mathematics, Physics or related fields
• Experience in a Data Science related role
• Hands-on experience in building segmentation and prediction models with large datasets using various algorithms and techniques (decision trees, logistic regression, neural networks, clustering, etc.)
• Hands-on experience in Python and common numerical and ML packages (NumPy, SciPy, Scikit-Learn, Pandas, Keras, TensorFlow, PyTorch, and PySpark)
• Good software engineering practices e.g. unit tests, logging, CI/CD pipelines, software patterns and experience developing production software
• Sound knowledge of classic prediction processes (classification, regression, ranking, time series), and inferential statistics (tests, interpretation of models)
• Experienced dealing with large amounts of data and knowledge of big data technologies (e.g. SageMaker, AirFlow, Snowflake, Looker)

Benefits

• Autonomy, Impact, Collaboration, Learning & Growth
• Being part of a profitable company in full-blown scale-up phase – offering immense opportunities for personal & career growth
• Flexible working hours, a hybrid work environment and/ or full remote
• Spend 5% of your working time on personal learning and development
• Conference / Training budget
• Food allowance of 7.62 euros per worked day
• Health insurance to all employees
• Company training in different areas
• Company equipment
• Company Events
• Extra Annual leave days (total 24)