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)