

Magnit
Financial Crime Analytics Lead
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Financial Crime Analytics Lead for a 5-month contract at £600 per day, based in London/Hybrid. Requires expertise in transaction monitoring, financial crime detection, and advanced analytics, with proficiency in Python and familiarity with AML regulations.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
640
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🗓️ - Date
February 13, 2026
🕒 - Duration
3 to 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Inside IR35
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Spark (Apache Spark) #Scala #Monitoring #Oracle #Model Validation #Data Science #Python #Data Engineering #SAS #Compliance #Programming #Snowflake #Databricks #SQL (Structured Query Language) #Pandas
Role description
Financial Crime Analytics Lead
5 month contract, £600 per day inside IR35
London/Hybrid, 3 days in the office
My client are a Global Banking organisation seeking a highly skilled Financial Crime Analytics Lead or Data Scientist to join their EMEA Financial Crime Operations team. You will work within the Intelligence & Analytics function, responsible for enhancing the effectiveness of transaction monitoring and sanctions screening systems. This is a hands-on, data-driven role with a focus on leveraging advanced analytics, optimisation techniques, and model validation to strengthen financial crime detection across multiple jurisdictions.
This role will suit an expert in Financial Crime Analytics or a Data Scientist with background in transaction monitoring and sanctions.
Key Responsibilities:
• Lead a specialist analytics team to develop, optimise, and enhance segmentation, tuning, and monitoring logic in transaction monitoring and sanctions screening programs.
• Coordinate and implement detection scenarios to identify potential financial crime activity.
• Support the design, tuning, and optimisation of automated monitoring and sanctions screening models, ensuring high alert quality and efficiency.
• Contribute to the development and validation of models, including scenario calibration, segmentation logic, and optimisation frameworks.
• Collaborate with regional analytics teams to share learnings and implement global improvements in financial crime detection.
• Assist in updating policies, procedures, and governance frameworks related to transaction monitoring and sanctions screening activities.
• Translate complex analytical insights into actionable recommendations for operational teams, senior management, and regulators.
• Oversee model validation, memorialise assumptions, and ensure regulatory alignment with AML, sanctions, and financial crime compliance standards.
Key Skills/Experience:
• Proven track record in transaction monitoring and financial crime detection, with experience in sanctions screening highly desirable.
• Strong experience in a global banking organisations, consultancy, or regulatory environment, with strong analytical and problem-solving skills.
• Hands-on experience with data engineering and data science techniques: building scalable analytics pipelines, model development, and optimisation frameworks.
• Transaction monitoring system experience would be advantageous such as Actmize, Fiserve AML, SAS AML, FICO TONBELLER, Oracle Mantas.
• Advanced analytical tools and programming languages, experience of Python is essential, advantageous to have exposure to SQL, Spark, Databricks, Snowflake, Pandas, or similar.
• Strong knowledge of financial crime regulations, including AML, sanctions, and monitoring requirements across EMEA jurisdictions.
• Excellent written and verbal communication skills, with the ability to present complex analytical insights clearly to senior management and regulatory bodies.
• Degree or equivalent industry-standard qualification in a quantitative, technical, or finance-related discipline.
Financial Crime Analytics Lead
5 month contract, £600 per day inside IR35
London/Hybrid, 3 days in the office
My client are a Global Banking organisation seeking a highly skilled Financial Crime Analytics Lead or Data Scientist to join their EMEA Financial Crime Operations team. You will work within the Intelligence & Analytics function, responsible for enhancing the effectiveness of transaction monitoring and sanctions screening systems. This is a hands-on, data-driven role with a focus on leveraging advanced analytics, optimisation techniques, and model validation to strengthen financial crime detection across multiple jurisdictions.
This role will suit an expert in Financial Crime Analytics or a Data Scientist with background in transaction monitoring and sanctions.
Key Responsibilities:
• Lead a specialist analytics team to develop, optimise, and enhance segmentation, tuning, and monitoring logic in transaction monitoring and sanctions screening programs.
• Coordinate and implement detection scenarios to identify potential financial crime activity.
• Support the design, tuning, and optimisation of automated monitoring and sanctions screening models, ensuring high alert quality and efficiency.
• Contribute to the development and validation of models, including scenario calibration, segmentation logic, and optimisation frameworks.
• Collaborate with regional analytics teams to share learnings and implement global improvements in financial crime detection.
• Assist in updating policies, procedures, and governance frameworks related to transaction monitoring and sanctions screening activities.
• Translate complex analytical insights into actionable recommendations for operational teams, senior management, and regulators.
• Oversee model validation, memorialise assumptions, and ensure regulatory alignment with AML, sanctions, and financial crime compliance standards.
Key Skills/Experience:
• Proven track record in transaction monitoring and financial crime detection, with experience in sanctions screening highly desirable.
• Strong experience in a global banking organisations, consultancy, or regulatory environment, with strong analytical and problem-solving skills.
• Hands-on experience with data engineering and data science techniques: building scalable analytics pipelines, model development, and optimisation frameworks.
• Transaction monitoring system experience would be advantageous such as Actmize, Fiserve AML, SAS AML, FICO TONBELLER, Oracle Mantas.
• Advanced analytical tools and programming languages, experience of Python is essential, advantageous to have exposure to SQL, Spark, Databricks, Snowflake, Pandas, or similar.
• Strong knowledge of financial crime regulations, including AML, sanctions, and monitoring requirements across EMEA jurisdictions.
• Excellent written and verbal communication skills, with the ability to present complex analytical insights clearly to senior management and regulatory bodies.
• Degree or equivalent industry-standard qualification in a quantitative, technical, or finance-related discipline.






