Fraud Data Analytics Senior Consultant

About the role

We are partnering with a leading global organisation to hire a senior specialist in fraud data analytics. The team operates at the cutting edge of data‑driven fraud risk management, using machine learning, network and graph analytics, and large language models to uncover hidden risks and support high‑profile investigations for major financial institutions.

Key responsibilities

• Collaborate with clients, investigators, compliance, audit, legal and regulator teams on complex, sensitive engagements.
• Gather requirements, define scope and translate business challenges into analytical solutions.
• Deliver end‑to‑end analytics projects, including data acquisition, engineering, transformation, analysis, visualisation, deployment and stakeholder reporting.
• Analyse large volumes of structured and unstructured data to identify patterns, anomalies and potential risks.
• Develop models and algorithms for fraud detection, financial crime monitoring, misconduct investigations and regulatory compliance.
• Apply advanced techniques to detect suspicious transactions, behavioural patterns and emerging risks.
• Create clear visualisations and reports for technical and non‑technical audiences.
• Mentor junior team members and ensure high‑quality delivery across engagements.
• Work with technology, innovation and business development teams to drive continuous improvement.

Required profile

• Degree in Computer Science, Engineering, Mathematics, Statistics or equivalent practical experience.
• Strong hands‑on experience with Python, SQL and modern data platforms such as Databricks or Azure Data Factory.
• Proven ability to design and deliver data‑analytics solutions across the full project lifecycle.
• Excellent problem‑solving, critical thinking and analytical abilities.
• Clear communication of complex technical concepts to diverse stakeholders.
• Experience working independently, managing multiple priorities and mentoring less experienced colleagues.

Required skills

• Python
• SQL
• Databricks
• Azure Data Factory
• Machine Learning
• Network Analysis
• Graph Analytics
• Large Language Models