You will partner closely with the credit underwriting team. You will be comfortable exploring data to visualise and explain hypotheses and models.
Required skills and experience
- MS degree / PhD degree in a quantitative discipline (eg. stats, cs, physics) or equivelant.
- 3+ years of relevant working experience
- Applied experience with machine learning, deep learning solving problems at scale
- Ability to communicate business outcomes and recommendations from analysis verbally and written, ability to present results coh
- Ability to develop confidently in Python
- Confident extracting and manipulating data from our various SQL and NoSQL data stores and storage frameworks.
Preferred experience can include:
- Comfortable with big data stores (Google BigQuery, Amazon Datastores) and tools (including dynamoDB, elasticsearch, S3, SQS, Kinesis) or Spark / Storm / Hadoop / Kafka or Neo4.
- Expert technical and analytical skills who can really mine into the data and pull insightful customer behavioural patterns
- Practical experience with Recommender systems, LearningToRank
- NLP - Ontology learning & semantic classification, automation / conversational AI
- Experience in retail sector
- Experience working in agile teams, with code reviews and source control