Data Scientist - Credit Risk

Key Responsibilities / Deliverables

• Develop market leading statistical models for the credit reference agency part of the Equifax UK business e.g. Risk Navigator credit bureau scores, collections scores, fraud models, other risk scores, affordability solutions, income verification products and solutions to identify consumer vulnerability

• Utilise and blend all available data sources to ensure all models are highly predictive and market leading - consumer bureau, postcode insights, open source data & transactional insights

• Apply traditional model development techniques and approaches (e.g. linear & logistic regression) as well as adopting new AI/ML techniques such as gradient boosting, random forests, clustering, etc.

• Utilise the latest cloud based technologies and analytical tooling to support test and learn champion/challenger approaches towards new scores and models

• Consider the creation of new characteristics/attributes to improve and maximise the predictive power of the model(s) as well as enhancing and creating other analytical products and services

• Investigate and apply appropriate segmentation and sub-populations to maximise overall model & score performance

• Liaise with internal stakeholders in a timely and effective manner towards the delivery of new scores and products e.g. Product Managers, Model Risk Management, Pre-Sales, Consultancy, Compliance, Technology, Data & Analytics, etc.

• Work closely with Data Scientists and analytical teams globally across the Equifax business to share best practice and learnings

• Adhere to relevant model development policies and procedures towards a successful deployment of scores and models e.g. sample design, good/bad definitions, rationale for exclusions, model development, model validation, implementation, etc.

• Produce suitable documentation alongside the statistical development of the model(s)

Skills & Experiences - Essential

• Extensive experience developing statistical models and scores across the consumer lending cycle e.g. application scores/models, behavioural scores, collections & recoveries models, fraud, etc.

• Highly numerate with a relevant degree

• Use of relevant analytical tooling on a day-to-day basis e.g. Python, BigQuery, Jupyter Notebook, SQL, etc.

• Previous experience of developing regression models and scores - linear and logistic

• Day to day exposure to large/complex datasets, analytical tools, spreadsheets, analytical platforms, etc.

• Experience using credit bureau data in statistical models - raw and summarised data

• Able to extract data from multiple platforms and create master datasets towards the development of statistical models

• A team player, effective communicator with the ability to work unsupervised

Skills & Experiences - Desirable

• Experience of developing AI/ML based solutions and models

• Day to day use of G-Suite tooling, GCP and VertexAI

• Experience of working in a credit reference agency and/or client environment e.g. Banking, Lending, Insurance, Public Sector, Utilities, etc.

• Use of alternative data such as open banking transactional data in statistical models

• Experience of working in a product development environment

• Experience with standard product testing procedures (UAT, OAT, regression, etc.)

• Adoption of champion/challenger approaches and techniques

• Creative and innovative thinker

• Strong track record of delivery

• Team player with the ability to go above and beyond