The QA Fraud Detection team protects Barclays customers and shareholders from the adverse consequences of fraud using predictive models based on machine learning techniques.
These models are key components of Global Fraud Management's fraud prevention strategies and Fraud Detection and are responsible for both developing internal models and the oversight of vendor models. The models are used to predict application and transaction fraud on consumer and wholesale products across all Barclays business units.
The team uses a variety of modeling techniques such as linear regression, random forests and gradient boosted machines, primarily on Hadoop infrastructure with the latest tools and very large sets of data. The team is located in London, New York, Wilmington and Noida. The Head of QA Fraud Detection will lead a team delivering high performing fraud detection machine learning models for use by Global Fraud Management on the Barclays US portfolio.
*You will lead a team of Data Scientists developing and managing machine learning models for fraud detection, creating a culture of integrity, excellence and relentless team development and improvement.
*You will be a trusted consultant to Global Fraud Management (GFM) and Technology stakeholders on fraud detection modeling, influencing model related decisions to reach great solutions.
*You will plan and deliver high performing fraud detection models for the BUS portfolio, meeting agreed deadlines and ensuring accurate, efficient implementation of models in production systems.
*You will own the management of live Fraud Detection models delegated from model owners on the BUS portfolio, including annual reviews, performance monitoring reviews, retrains and remediation activity.
*You will enforce adherence to the Barclays Model Risk Governance Framework and regulatory requirements for all models, documented robustly and demonstrated at appropriate committees.
*You will keep abreast of machine learning and fraud detection industry developments, conducting R&D to incorporate best in class modeling methodologies and disseminating learnings to the wider QA team.
*A Bachelor's degree in a numerate subject (such as math, statistics, computer science or physics)
*5 years' experience of credit or fraud risk management practices in a Financial Services company, with understanding of model usage, technology and governance.
*5 years' experience developing and implementing predictive machine learning models on large data sets using tools such as R, Python and Spark.
*3 years' experience managing Data Scientists to deliver models, including project planning and relationship building with model owners and other stakeholders.
*Recent experience developing and implementing machine learning models (e.g. Random Forests, Gradient Boosted Machines and Deep Neural Networks) in a financial services company for fraud risk management.
*Ability to take cutting edge data science and machine learning research and translate it into value-adding business projects leveraging the newest algorithms and technology.
*Experience leading Data Scientist teams across multiple locations delivering several concurrent projects.
*PhD or Master's degree in a numerate subject and certificates in Machine Learning courses.
Barclays' U.S. headquarters is located at 745 Seventh Avenue in New York, NY. At Barclays, we offer you an engaging and challenging environment, giving you the opportunity to make the most of your unique set of skills. We also have an extensive range of learning and development initiatives designed to support you both personally and professionally. In 2017, Barclays announced plans to create a world-class campus in Whippany, New Jersey, for our Technology, Operations and Functional teams in the US. The Whippany campus will play an important role in Barclays' future, bringing together a number of Chief Operating Office (COO) and Functions teams in a single state-of-the-art work environment and will become one of the flagship sites in our global footprint.
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