Data Scientist - Commercial

The role
We are looking for a Data Scientist to join our effort in Machine Learning (ML) for Commercial. 
We want to optimise, automate, and test our planning and pricing actions on over 300,000 products on the Farfetch marketplace. As the largest luxury fashion platform we work with over 3000 brand and boutique partners giving us an unrivalled breadth of stock, this creates a wide range of data science opportunities  to make an impact by optimising our planning and pricing strategy.
In particular, we are seeking to optimise the supply we obtain and the price over the lifecycle of our products. The objective is to be able to optimise, measure, and adapt our planning and pricing strategy in an automated way aligned with business needs.
We are a pragmatic team and pick whatever technique is appropriate for the task at hand (including but not limited to Deep Learning, Gradient Boosting, Graph Modelling, Recommender Systems, etc), keeping an eye to what is happening in academia and in the industry to stay on top of recent developments. We work in Python running on a Kubernetes cluster in Google Cloud.
We are looking for someone who is a self-starter, willing to own complex projects from start to finish and ensure their delivery. This will require working with engineering teams to productionise and integrate data science solutions with the relevant internal business products.

What you'll do

• Design and develop state of the art ML algorithms focusing in particular on time series forecasting and pricing optimisation;
• Design and implement experimentation around planning and pricing initiatives to measure impact on business KPIs and retrieve data for model building;
• Collaborate with the engineering team to integrate ML algorithms into our backend or connect them to third-party tools;
• Communicate complex solutions in a clear and understandable way to both experts and non-experts.

Who you are

• You have a MSc or PhD in Machine Learning, Statistics, Mathematics or other quantitative discipline;
• You have relevant industry experience in a Machine Learning or Data Science role, ideally with exposure to Marketing problems;
• Experience in Python software development (ideally on production-grade code, including code reviews, agile development, version control etc) and familiar with ML/scientific packages (e.g. Pandas, numpy, scipy, scikit-learn, gensim, keras, TensorFlow, PyMC3, PyStan, nltk, spacy);
• You have experience in using state of the art ML techniques in a business setting, such as Bayesian modeling, neural networks, graph ML, reinforcement learning etc, or a keen interest to learn.