AVP - AML Data Scientist (Hybrid)

The Data Science Senior Analyst will work under the supervision of a Functional Team Manager to provide ongoing support in terms of required analysis. The scope of analysis will cover all aspects of analysis performed by the team within different projects: Key Performance Indicator Driven Tuning and Tactical Tuning tasks, and data modeling/validation efforts depending on current needs and project plans. 

The Data Scientist will follow the globally consistent methodology but is expected to have a high level of initiative and creativity and suggest enhancements to current methodologies. The analyst evaluates moderately complex and variable issues with substantial potential impact, where development of an approach/taking an action involves weighing various alternatives and balancing potentially conflicting situations using multiple sources of information. It requires good analytical skills to filter, prioritize and validate potentially complex and dynamic material from multiple sources. Strong communication skills are required. Work and performance of all teams in the area are directly affected by the performance of the individual.

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.
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  Competencies:
• Very good written and verbal communication ability in an educational style. Ability to express thoughts and concepts clearly.
• Teamwork:  Ability to work well with a variety of people and to show team-player attitude regardless the scope of responsibilities.
• Creativity: Provide input into the innovation of new and enhanced approaches. Having initiative and a proactive attitude is desirable.
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Educational Qualifications:

• Bachelor’s Degree in Statistics, Mathematics, Data Science, Data Analytics, Business Analytics, or related quantitative fields
• Master’s Degree preferred
• Experience and knowledge in banking and finance will be desirable

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In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

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Anticipated Posting Close Date:

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Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

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