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**_Senior Applied Analytics Manager_****_Role Purpose:_****Financial Crime (FC) focuses on the specific financial crime threats the firm faces now and in the future, pioneering the techniques and technology that protect our business, our customers, and the many communities in which we operate from the harms associated with financial crime.
FC harnesses intelligence, analytics, technology, investigation, information sharing, and public-private partnership to achieve this end, always seeking the most effective and efficient means.
FC is also partnering with other areas in Compliance to build the case for a more efficient and effective regulatory approach by defining a potential new regulatory landscape based on practical,
tested innovation and serving as a thought leader in the ongoing public debate on the future of regulatory compliance.
****The LAM Applied Analytics Lead will help to develop and build an industry-leading, proactive, innovative and experimental research analytics team focused on providing cutting-edge analytic support to intelligence and investigations while pioneering ground breaking industry-first techniques for discovering and targeting actual financial crime risk.
The nature of the role requires strong mathematical background and programming oriented to data analysis.
****In this role, the jobholder is responsible for**:- **Leading a regional team of data scientists in pioneering new and ground breaking intellectual property to drive systemic management of risk across the bank.
**:- **Promoting the conceiving, development, testing, and validation of incremental and disruptive analytic techniques to protect the bank and predict financial crime threats.
**:- **Delivering a proactive plan of research and experimentation,
aligned to the bank's core financial crime threats and programme of analysis.
**:- **Provide thought leadership about the future direction of transaction monitoring, insider risk and risk modelling to better identify actual financial crime risks.
**:- **Promote more efficient and effective outcomes across investigations and analysis, allowing for rapid iteration and deployment of a variety of experimental techniques into operational systems.
**:- **Delivering a data-driven approach to strategic risk modelling for financial crime risk**:- **Providing high-touch tactical support for complex investigations and networks and iteratively testing analytic methodologies against known and discovered threat activities.
**:- **Recruiting and managing a high-performing team of data scientists, data analysts and quantitative analysts,
ensuring their development and engagement on active mitigation of financial crime risks.
**:- **Ensure experimental techniques are rigorous and purpose-built to allow for ease of approval, regulatory scrutiny, and independent validation.
**Requirements**Principal Accountabilities**:**Impact on the Business**- To manage a team of data scientists and quantitative analysts in region
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