Financial Crime Data Analyst

Financial Crime Data Analyst – BCB Group

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We are looking for a Financial Crime Data Analyst to be part of BCB's Data team and deployed full time within the Financial Crime Operations team to build and own our data analytics capabilities. You will be the bridge between our vast data resources and our operational teams, enabling a proactive, intelligence‑led approach to combating financial crime.

Reporting to the Head of Financial Crime Operations, you will be the firm's subject matter expert on all things related to financial crime data. You will have the autonomy to design the infrastructure, develop the analytics, and embed a data‑first culture that will fundamentally enhance how we protect our clients and the firm.

Your mission is to establish a data‑driven foundation for our financial crime framework, transitioning the team from manual data handling to a modern, analytics‑powered approach to detecting and preventing financial crime and work hand in hand with AI.

• Data Infrastructure & Engineering: Take full ownership of the Financial Crime Operations team's data needs, from extraction to storage. Collaborate with the tech team to design and build robust data pipelines, ensuring the team has reliable and timely access to the data it needs.
• Proactive Analysis & Intelligence: Work extensively with data to identify fraud trends, analyse case specifics, and draw insightful, evidence‑based conclusions. Proactively analyse complex datasets, particularly client transactional data, to identify emerging patterns and hidden risks. Conduct deep dives into various Fincrime systems for fraud detection, transaction monitoring and customer risk to identify key business opportunities.
• Process Transformation: Lead the transition from manual, spreadsheet‑based data processes to a scalable and efficient data environment. Ensure our data storage and management practices are aligned with the firm's technology standards and expectations.
• AI & LLM Enablement: Prepare and structure datasets to be readily consumable by LLM models, driving efficiency and helping the team leverage cutting‑edge AI capabilities.
• Tooling & Visualisation: Champion the use of modern technology to build and maintain insightful dashboards and automated reporting. Leverage data to develop and implement effective MIs and KRIs to monitor our financial crime prevention program.
• Model Calibration & Assurance: Provide analytical support for the calibration, testing, and assurance of our Transaction Monitoring models to ensure they are effective and performing optimally.
• Stakeholder
  
  Collaboration:
  
  Serve as the primary subject matter expert on financial crime data across the business. Provide clear and insightful Management Information and strategic advice to senior stakeholders on data‑driven findings and opportunities.

• You will have proven, extensive experience in a data science, data analytics, or data engineering role, preferably within a financial crime, risk, or compliance function in the payments, crypto, or banking sectors.
• Strong proficiency in SQL and Big Query for complex data extraction, manipulation, and analysis is essential. Data modelling is a bonus.
• Hands‑on experience with a programming language like Python and Type Script for data analysis, scripting, and automation.
• Demonstrable experience with data visualisation, BI tools (e.g., Looker) and a proven ability to tell a compelling story with data, supported by good dashboards and data presentation.
• A decisive, hands‑on professional who is comfortable defining a vision, building solutions from the ground up, and owning outcomes in a fast‑paced environment.
• Experience in building data pipelines and working with engineering teams to establish best practices for data storage and management.
• Exceptional analytical and problem‑solving skills, with the ability to synthesise complex information and distil it into practical advice for non‑technical audiences.
• Strong communication and interpersonal skills, with the ability to build and maintain effective relationships with internal stakeholders.
• Autonomo…