Fraud Data Senior Consultant
Senior Data Analytics Consultant – Fraud & Investigations
London
About the Opportunity
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.
Key Responsibilities
- 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.
What We're Looking For
- 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.
Desirable Experience
- 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