Fourth is no ordinary product software company.  We pride ourselves on unique cloud-based SaaS used by several million users which enables hotels, restaurants, bars, and pubs to improve efficiency and save money whether they're buying stock, scheduling staff, or creating recipes.  

 

Role overview: 

 

The Data Scientist will be an integral part of the Data Science Team at Fourth. The role fits into our broader team together with ML Engineers, Data Engineers and Data Analysts.

The focus will be to build data-powered solutions forming part of our product. Such solutions are typically linked to demand prediction, labor prediction, inventory and intra-day planning. The main purpose of the Data Scientist is to define and execute data science experiments, to create PoC and to move them to production with support from ML and Data Engineers.  

Most of the work is done in Python (with various packages and extensions: pandas, sklearn, Tensorflow, PyTorch, scikit-learn etc.).

 

Your daily job will include: 

 

· Exploratory data analysis 

· Feature engineering 

· Time series forecasting 

· Model development 

· Model deployment 

· Model monitoring 

· A/B testing 

· Using strong business acumen, as well as the ability to communicate findings, and mine vast amounts of data for useful insights 

· Using these insights to influence how an organisation approaches business challenge 

· Using a combined knowledge of computer science and applications, modelling, statistics, analytics and maths to solve problems 

· Sifting and analysing data from multiple angles, looking for trends that highlight problems or opportunities 

· Communicating important information and insights to business and IT leaders 

· Making recommendations to adapt existing business strategies 

 

Experience and competencies needed: 

 

· Strong statistical and machine learning knowledge 

· Strong coding skills (clean and commented code, version control, documentation) 

· Ability to develop high-performing end-to-end machine learning models (data processing, feature engineering, model training, scoring, monitoring) 

· Experience with feature engineering using Python, SQL or similar tools 

· Experience with machine learning using Python, Spark, PyTorch, scikit-learn or similar languages and libraries 

· Experience with visualisations and communication of data science insights and results to business people 

· Experience with time series forecasting is a big plus. 

· Familiarity with containerisation of data and ML pipelines, ML CI/CD and monitoring of data, code and models in production is an advantage 

 

 

· 25+ days off, as well as birthday day off and 4 charity days off per year

· Flexible start and end of the working day and hybrid working mode, including a combination remote and in the office 

· Personal career development plan, learning paths and mentorship

· Team-centric atmosphere

· Competitive salary package

· Encouraging healthy lifestyle and work-life balance including supplemental health insurance

· New parents bonus scheme

*Only short-listed candidates will be contacted.