Data Scientist - Fraud

What You’ll Do

What experience you need

What could set you apart

Responsibilities

• Develop market leading statistical fraud models and pseudo-models for the Equifax UK business e.g. consumer fraud models, commercial fraud models, synthetic fraud, payment intent models, and loan stacking indicators and models Utilise and blend all available data sources to ensure all fraud models are highly predictive and market leading - consumer bureau data, postcode insights, open source data,transactional insights & fraud indicators from partnerships
• Apply traditional model development techniques and approaches (e.g. 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 fraud 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. This can be done through expert approaches or through AI approaches (e.g. transformers)
• 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) to support peer review and Model Risk Management processes
• What experience you need
• Experience using credit bureau data in statistical fraud models - raw and summarised data
• Extensive experience developing statistical models and scores particularly within fraud (consumer and commercial)
• Highly numerate with a relevant degree 2:1 or above
• Use of relevant analytical tooling on a day-to-day basis e.g. Python, SAS, BigQuery, Jupyter Notebook, SQL, etc.
• Previous experience of developing regression models and scores - e.g. logistic
• Day to day exposure to large/complex datasets, analytical tools, spreadsheets, analytical platforms, etc.
• Able to extract data from multiple platforms and create master datasets towards the development of statistical models
• Experience across different fraud types, e.g. consumer fraud, commercial fraud, Anti-Money Laundering, KYC.
• A team player, effective communicator with the ability to work unsupervised
• Understanding of the regulatory landscape with respect to consumer & commercial credit and the potential impact to our clients (i.e. addressing the "why" behind our decision making)
• What could set you apart
• Experience of developing AI/ML based fraud 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 LLMs to improve efficiencies in the model building process
• Use of alternative data such as open banking transactional data in statistical models
• Experience of working in a product development environment
• Experience with industry related fraud prevention tools (e.g. Hunter, Kount, SEON, ThreatMetrix, Lexisnexis, Minerva, CrossCore, TruValidate, FICO Falcon, etc.)
• 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
• The Perks of being a Equifax Employee?
• We offer a wide range of company supported benefits including contributory pension, life cover, income protection, healthcare, enhanced maternity and sick pay, 26 days holiday and a day off for your birthday, with the ability to buy and sell and free credit checks. We also offer flexible benefits ranging from cycle to work, discounted travel options, gym membership, dining and leisure discounts, financial & savings plans, mobile discounts plus much more!
• We also support personal development and have a range of learning options including our global online learning platform and allow you to bring your whole self to work supported by our Inclusion and Diversity, Wellbeing and Employee Engagement forums.
• Are you ready to power your possible? Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference!
• Primary Location:
• Function