Responsibilities:

• Apply quantitative and qualitative data analysis methods including Python/ SAS/ R, SQL to extract, transform and analyze data.
• Prepare statistical and non-statistical data for visualization and exploration, validate data, identify data quality issues in AML risk related projects.
• Contribute towards AML Optimization techniques and related deliverables i.e. Optimizing monitoring systems, document optimization solutions, and present results to non-technical audiences; write formal documentation using statistical vocabulary;
• Build Machine Learning (Predictive Modeling/ Classification/ Regression) models.
• Conduct data analysis, data mining, read and create formal statistical documentation, and work with Technology and Sponsors to address issues.
• Analyze and interpret data reports, make recommendations addressing business needs.
• Validate assumptions, escalate identified risks and sensitive areas in methodology and process.
• Automate recurring data extraction and data pre-processing tasks, perform ad-hoc data analyses, and provide documentation and presentations.
• Appropriately assess risk when business decisions are made keeping in mind the firm's reputation by being compliant with applicable laws, rules and regulations and adhering to Policy.
• Apply sound ethical judgment regarding personal behavior, conduct and business practices, and escalate, manage and report control issues with transparency.

Qualifications:

• Strong statistical academic background, knowledge of quantitative methods, including predictive modeling techniques.
• Experience in creating and assessing Statistical Models.
• Good working knowledge of Python/ SAS/ R & MS Office Suite.
• Experience in reporting the results of analysis in clear written form, and in presenting the findings during meetings and conference calls.
• Team working experience (demonstrated team player ability required).
• Understanding of technical requirements, ability to communicate with Technical Support.
• Ability to manipulate data using SQL or equivalent.
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  Desirable:
• Experience with data exploration
• Mantas and AML monitoring systems experience or other transaction monitoring systems a plus.
• Knowledge of the local/regional laws and regulations applicable to anti-money laundering a plus.
• Previous experience with financial services companies (retail banking, small business banking, commercial, institutional, private banking).
• Knowledge of any programming language or dedicated statistical software would be an advantage.

Skills:

• Statistical/data analytical skills - including both calculation and interpretation of outcome.
• Methodical analysis and problem-solving skills.
• Initiative, creativity and attention to detail are essential.
• Ability to work under close supervision of a functional team manager, while preserving independence of thinking and responsibility for the results.
• Ability to discuss reasoning, critical assessment of facts and opinions; ability of giving comprehensive answers and arguments.
• Conceptual and creative thinking (outside the box).
• Demonstrated ability to communicate effectively, both orally and in writing, through all levels of the organization and through different business units.
• Self-motivated with high desire of self-development and learning.
• Must be able to coordinate and deal with conflicting time demands.
• Ability to work non-standard business hours, including weekends and holidays as determined by the business needs. Flexibility will be expected.