Fraud Data Scientist

Barclays Bank Plc; Northampton; On-site; GBP 55,000 - 75,000; Full time

Job summary

A leading financial institution in Northampton is seeking a Fraud Data Scientist to enhance fraud detection systems using advanced analytical methods. Ideal candidates will possess a strong background in fraud detection and cybersecurity, along with proficiency in languages like Python and SQL. The position offers an opportunity to collaborate with experts in mitigating fraud risks while leading a team. Competitive compensation and growth opportunities await.

Qualifications

• Strong background in fraud detection and cybersecurity.
• Experience in the financial services environment related to data analysis.
• Hands-on proficiency with data analysis tools and frameworks.

Responsibilities

• Develop fraud detection systems using advanced analytical methods.
• Collaborate with experts to mitigate fraud risks.
• Supervise and guide a team in achieving targets.

Skills

Data analysis

Python

R

SQL

Machine learning

Fraud detection

Education

Degree in Mathematics, Statistics, or Computer Science

Job description

Overview

Purpose of the role: To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.

Responsibilities

• Identify, collect, and extract data from various sources, including internal and external sources.
• Perform data cleaning, wrangling, and transformation to ensure quality and suitability for analysis.
• Design and maintain efficient data pipelines for automated data acquisition and processing.
• Design and conduct statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Develop and implement predictive models to forecast future outcomes and identify potential risks and opportunities.
• Collaborate with business stakeholders to identify opportunities to add value from data through Data Science.

Analyst/Leadership Expectations

• Perform prescribed activities in a timely manner and to a high standard, consistently driving continuous improvement.
• Demonstrate in-depth technical knowledge and experience within the assigned area of expertise; have a thorough understanding of underlying principles.
• Lead and supervise a team, guiding and supporting professional development, allocating work requirements, and coordinating team resources.
• Demonstrate leadership behaviours where applicable: Listen and be authentic, Energise and inspire, Align across the enterprise, Develop others. For individual contributors, develop technical expertise and act as an advisor where appropriate.
• Take responsibility for end results of a team's operational processing and activities. Escalate breaches of policies/procedures appropriately. Embed new policies/procedures adopted due to risk mitigation.
• Advise and influence decision making within own area of expertise; manage risk and strengthen controls related to your work.
• Deliver work in line with rules, regulations, and codes of conduct; understand how your sub-function integrates with the broader organisation.
• Make evaluative judgments based on analysis of factual information and detail-oriented problem solving guided by precedents.
• Guide and persuade team members and communicate complex or sensitive information. Act as a point of contact for stakeholders outside the immediate function and build networks outside the team and organisation.
• Demonstrate Barclays Values of Respect, Integrity, Service, Excellence and Stewardship, and embody the Barclays Mindset to Empower, Challenge and Drive.

Role Specifics

• Fraud Data Scientist at Barclays: responsible for the development and enhancement of fraud detection systems. Apply advanced analytical methods and data-driven approaches to improve the ability to detect and prevent fraud across banking products and services.
• Collaborate with other experts to stay ahead of fraud risks.
• Location: Northampton office.

Qualifications and Skills

• A Degree in Mathematics, Statistics, Computer Science, or a related field (or equivalent work experience).
• Experience in fraud detection, scam prevention, or cybersecurity, ideally in a financial services or banking environment.
• Proficiency in data analysis with hands-on experience using Python, R, SQL, and machine learning frameworks.
• Ability to assess key critical skills relevant for success in role, including risk and controls, change and transformation, business acumen, strategic thinking, and digital/technology competencies.