Data Scientist - Investment Bank

Development and management of machine learning models.

- Delivery of high performing fraud detection models for BUK and BI portfolios, meeting agreed deadlines and supporting accurate, efficient implementation of models in production systems.

- Perform annual reviews, performance monitoring reviews, retrains and remediation activity on models as required.

- Ensure all deliveries conform to Barclays Model Risk Governance Framework and regulatory requirements and produce robust, clear documentation.

- Keep abreast of machine learning and fraud detection industry developments, incorporating best in class modelling methodologies into projects.

What we- re looking for:The role requires an independent thinker with data science knowledge, able to use sophisticated analytical techniques to reduce fraud losses and improve Barclays- customer experience. The role holder must be able to translate technical concepts into implementable solutions, whilst communicating results and benefits clearly to stakeholders.

- Strong analytical skills with experience developing predictive machine learning models, ideally on large data sets in Hadoop environments using tools such as Python, Spark and MLLib.

- Understanding of credit or fraud risk management practices in a Financial Services company and familiar with model usage, technology and governance.

- A Bachelor's degree in a numerate subject (such as maths, statistics, computer science or physics).

Skills that will help you in the role:

- Experience developing and implementing the latest 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.

- PhD in a numerate subject and certificates in Machine Learning courses.