We’re a Data team that does it all : big data engineering, state-of-the-art machine learning, and deep dive analytics and insight.
We’re a diverse, global team who create innovative Data solutions to provide an unrivalled customer experience. Whether it’s churning gigabytes of ecommerce data, using AI to recommend the latest trends, or understanding our customers better than anyone else, we eat, sleep and breathe data so that we can drive Farfetch’s growth.
As a member of the Inspiration data science team, you will play a key role in the establishment of a new platform, with opportunities to create enormous benefits for Farfetch customers.
You will design and implement deep learning models (e.g., graph embeddings) to fit various use cases, productionise machine learning algorithms, and provide expertise around graph data modelling and ontology design.
In return you can expect an opportunity to shine, plenty of support from a talented team, and a friendly and positive working environment.
What you'll do :
Prototype, test, and productionise machine learning pipelines to recognise entities in a knowledge graph and infer new knowledge (e.
g., Knowledge Base Population, Relation Extraction, Entity Matching, Named Entity Recognition, etc..)
Independently evolve the ontology for a fashion knowledge graph
Provide solutions for problems with substantial commercial impact
Perform analysis to identify challenges and opportunities, deriving valuable insights
Conduct experiments to show causal impact of new ideas or implementations
Who you are :
Deep understanding of embedding methods (ideally graph embeddings), and Deep Learning in general.
Extensive experience writing clean and concise production-ready code in Python and at least one of Bash, Go, or JSAre proficient in or highly enthusiastic to rapidly develop skills in designing ontologies and graph data modelling using tools like Neo4j and Cypher, or the RDF Semantic Web stack
Have a solid understanding of Natural Language Processing, ideally utilising deep learning techniques with TensorFlow
Experience in analysing data using statistical techniques and conducting experiments using SQL and Python libraries such as Pandas
Are extremely capable of working with machine learning software - having a working knowledge of productionising models : Git version control, unit tests, and containers
Work well as an individual and as part of a team that loves to deploy best practices
Have a strong ability to abstract complex problems to their essential components and design and implement elegant solutions for them