Drive strategic initiatives that enhance analytical capabilities to detect and mitigate financial crime and risk
Optimize data-driven solutions for financial crime prevention and risk intelligence
Strengthen analytics infrastructure to support financial crime detection and risk management
Elevate the strategic use of analytics in combating financial crimes and assessing risk exposure
Refine and scale analytical frameworks for financial crime insights and risk evaluation
Drive innovation in analytics to uncover financial crime patterns and emerging risk trends
Modernize analytics platforms using AI tools to improve financial crime surveillance and risk forecasting
Deploy targeted analytics to support proactive financial crime intervention and risk controls
Transform raw data into actionable intelligence for financial crime and risk operations
Integrate advanced analytics into financial crime strategy and enterprise risk oversight
Requirements
Proven experience in data analytic
Experience in financial crime analysis is highly desired
Strong relationship management and stakeholder engagement skills
Ability to solve big and ambiguous problems using data-driven strategies
Experience with Bloomberg and Morningstar for industry insights
Excellent communication and storytelling skills
Strong ability to influence and collaborate with senior stakeholders to drive strategic initiatives and achieve business objectives
Strong understanding of marketing mix modeling techniques, including multivariate regression and time-series analysis
Ability to analyze large datasets from various channels to understand the impact of different financial crimes activities and other key performance indicators
Proven track record in developing and maintaining advanced statistical models to estimate the effectiveness of marketing tactics and predict future performance
Experience with tools and technologies such as Tableau, Power BI, Python, SQL, Redshift, AWS
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