VP, Financial Crime Data Insights & Analytics

SMBC Group; England; Hybrid; GBP 60,000 - 85,000; Full time

Benefits offered by this job

Hybrid working

Private medical insurance

Learning & development

Competitive benefits

Job summary

SMBC Group is seeking a highly skilled Financial Crime Data Analyst to leverage data-driven insights in the fight against financial crime. The role focuses on data management, analytics, modelling, and communicating findings related to customer due diligence and risk assessments.

You will support the Bank’s CDD program through advanced analytics, improving data management, modelling, monitoring and reporting capabilities, and identifying patterns, trends and risks within CDD activities.

Qualifications

• Experience in a data analytics role, preferably within financial crime, risk or compliance in financial services.
• Strong background in data analytics, data science, or quantitative analysis (SQL, Python, R, SAS or similar).
• Knowledge of Customer Due Diligence and regulatory frameworks.

Responsibilities

• Design and run advanced SQL queries on large financial data to identify patterns and anomalies.
• Translate datasets into dashboards and MI reports for senior stakeholders and regulators.
• Analyse customer due diligence data to detect and communicate financial crime risks and trends.
• Develop and own dashboards, reports and metrics for CDD and customer risk models.
• Lead deep-dive modelling and report insights to policy and model owners.

Skills

SQL

Python

R

Data analytics

Communication skills

Education

Degree in Data Science

Degree in Mathematics

Degree in Statistics

Tools

Tableau

Power BI

Qlik

Camunda

Fenergo

Job description

SMBC Group is seeking a highly skilled Financial Crime Data Analyst to leverage data-driven insights in the fight against financial crime. The role focuses on data management, analytics, modelling, and communicating findings related to customer due diligence and risk assessments.

You will support the Bank’s CDD program through advanced analytics, improving data management, modelling, monitoring and reporting capabilities, and identifying patterns, trends and risks within CDD activities.