.The Senior Analyst will join the Global AML Business Systems, Data & Analytics' under the ML Detection and Client Insights function. The role will have a key focus of supporting the continued development of the technical solutions that support AML. The Senior Analyst will work closely with the AML Functions and all levels of AML staff from across all the regions, including our Regional and Country Hubs. The role will work alongside Compliance and Technology in support of the project and initiatives. The individual will also interact with Compliance teams and potentially other Citi businesses outside of AML.The Senior Analyst will play a strategic role in Global AML Business Systems, Data & Analytics in formulating platform strategy, projects and programs with a Technology focus, addressing business/functional requirements across the AML product family (Monitoring, Detection, KYC etc.)The ideal candidate will have previous experience with Technology implementations, business and data analysis preferably with experience in the AML arena. They will be highly motivated, committed, and passionate about change, and meet quality assurance standards. Ideally from a technology, analytics or operations program background, they will have experience of leading and influencing people and a strong track record of successful technology project delivery and "making things happen." They will have excellent interpersonal skills and written and oral communication skills. They will also be an effective listener and, when required, be able to facilitate team and client meetings. Candidate must have an ability to deal with all levels of management and be self-motivated with the ability to make decisions in the absence of detailed instructions.OverviewThe System, Data & Analytics Senior Analyst must demonstrate critical thinking, analytical and problem solving abilities, hands-on intelligence or data analysis skills, network analysis acumen, and intellectual curiosity is essential for data science tasks. The candidate must be able to apply these abilities to detect non-obvious risks or develop, test, and champion ideas to increase detection. The candidate should understand data science methods, and visualization techniques to leverage internal and external data to identify and develop ways to systemically detect financial crime risk.Responsibilities:Utilize features and algorithms to drive down false positives and identify financial crime threats across the firm.Demonstrate an ability to apply curiosity and critical thinking in data mining, analytics, and derivative outputs.Conduct data mining / query functions across relational or big data databases utilizing various data science tools and methods.Supports global/regional internal SMEs; responsible for investigating and researching the Financial Crimes processes and tools identifying efficiency and effectiveness opportunities