Fraud Data Analytics Senior Consultant

We are partnering with a leading global organisation to recruit a fraud data analytics specialist.

The team works at the forefront of data-driven fraud risk management, leveraging technologies such as machine learning, network analysis, graph analytics, and large language models to uncover hidden risks, identify suspicious behaviour, and support high-profile investigations.

This is an excellent opportunity to work on impactful projects with major financial institutions and multinational organisations, helping them detect, prevent, and investigate fraud and misconduct.

• Partner with clients, investigators, compliance teams, auditors, legal professionals, and regulators on complex and sensitive engagements.

• Gather requirements, define project 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 from diverse sources to identify patterns, anomalies, and potential risks.

• Develop analytical models and algorithms to support fraud detection, financial crime monitoring, misconduct investigations, and regulatory compliance initiatives.

• Apply advanced analytical techniques to detect suspicious transactions, behavioural patterns, and emerging risks.

• Create compelling visualisations and reporting outputs that clearly communicate findings to technical and non-technical stakeholders.

• Mentor and support junior team members, ensuring high-quality delivery across engagements.

• Collaborate with technology, innovation, and business development teams to drive continuous improvement and growth.

• Degree in a STEM discipline such as Computer Science, Engineering, Mathematics, Statistics, or equivalent practical experience.

• Strong hands-on experience with Python, SQL, and modern data platforms such as Databricks, Azure Data Factory, or similar technologies.

• Experience designing and delivering data analytics solutions across the full project lifecycle.

• Excellent problem-solving, critical thinking, and analytical skills.

• Ability to communicate complex technical concepts clearly to a wide range of stakeholders.

• Experience working independently while managing multiple priorities and mentoring less experienced colleagues.

• Exposure to financial crime, fraud, regulatory compliance, investigations, market surveillance, or risk management environments.

• Consulting or client-facing experience.

• Experience with:

  • Relational databases (SQL Server, PostgreSQL, Oracle, MySQL)

  • Data visualisation tools (Power BI, Tableau, Spotfire)

  • Cloud platforms, particularly Microsoft Azure

  • Big data technologies (Spark, Elasticsearch, Hadoop)

  • Statistical modelling and advanced analytics

  • Machine learning and pattern recognition techniques

  • Web technologies such as HTML and JavaScript