Fraud Analytics Scientist - ML & Risk Insight

Barclays Capital; Northampton; On-site; GBP 70,000 - 110,000; Full time

Job summary

Barclays is seeking a Data Scientist to lead the evolution of our analytical capabilities and to apply advanced data analytics and machine learning to extract insights from the bank's data reserves. These insights will inform fraud detection systems to detect and deter fraudsters and to protect clients.

You will develop and maintain data pipelines, build predictive models, and collaborate with stakeholders to drive value across the organisation, contributing to the analytics optimisation

Qualifications

• Proficiency in SQL, SAS, Python or similar languages.
• Strong knowledge of fraud detection systems.
• Hands-on experience working with large and complex data sets.

Responsibilities

• Identification, collection, extraction of data from various sources, including internal and external sources.
• Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
• Development and maintenance of efficient data pipelines for automated data acquisition and processing.
• Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
• Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.

Skills

SQL

SAS

Python

Fraud detection systems

Large datasets

Job description

Barclays is seeking a Data Scientist to lead the evolution of our analytical capabilities and to apply advanced data analytics and machine learning to extract insights from the bank's data reserves. These insights will inform fraud detection systems to detect and deter fraudsters and to protect clients.

You will develop and maintain data pipelines, build predictive models, and collaborate with stakeholders to drive value across the organisation, contributing to the analytics optimisation