Citi Group Citi - Anti Money Laundering AML Statistician 

Mexico, Mexico City 

774009249

The Model/Anlys/Valid Sr Analyst is a seasoned professional role. Applies in-depth disciplinary knowledge, contributing to the development of new techniques and the improvement of processes and work-flow for the area or function. Integrates subject matter and industry expertise within a defined area. Requires in-depth understanding of how areas collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the function and overall business. Evaluates moderately complex and variable issues with substantial potential impact, where development of an approach/taking of an action involves weighing various alternatives and balancing potentially conflicting situations using multiple sources of information. Requires good analytical skills in order to filter, prioritize and validate potentially complex and dynamic material from multiple sources. Strong communication and diplomacy skills are required. Regularly assumes informal/formal leadership role within teams. Involved in coaching and training of new recruits

Responsibilities:

• Develops, enhances, and validates the methods of measuring and analyzing risk, for all risk types including market, credit and operational. Also, may develop, validate and strategize uses of scoring models and scoring model related policies.
• Conducts statistical analysis for risk related projects and data modeling/validation.
• Applies quantitative and qualitative data analysis methods including SAS programming, Structured Query Language (SQL) to extract, transform and analyze data and Visual Basic programming language.
• Prepares statistical and non-statistical data exploration, validate data, identify data quality issues.
• Conducts data analysis, data mining, read and create formal statistical documentation, reports and work with Technology to address issues.
• Analyzes and interprets data reports, make recommendations addressing business needs.
• Uses Predictive modeling methods, Optimizing monitoring systems, document optimization solutions, and present results to non-technical audiences; create formal documentation using statistical vocabulary.
• Generates statistical models to improve methods of obtaining and evaluating quantitative and qualitative data and identify relationships and trends in data and factors affecting research results.
• Validates assumptions; escalate identified risks and sensitive areas in methodology and process.
• Automates data extraction and data preprocessing tasks, perform ad hoc data analyses, design and maintain complex data manipulation processes, and provide documentation and presentations.
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.

Qualifications:

• 5-8 years experience
• Proficient in Microsoft Office with an emphasis on MS Excel
• Consistently demonstrates clear and concise written and verbal communication skills
• Self-motivated and detail oriented
• Demonstrated project management and organizational skills and capability to handle multiple projects at one time

• Bachelor’s/Universitydegree or equivalent experience

The scope of these analyses will cover all aspects of the work performed by IV across various Citi AML activities—e.g., optimization, segmentation, tactical tuning, KYC, etc.—depending on current needs and project plans. A primary area of focus for this position will be the validation of scoring models and scenarios for AML monitoring purposes.

The AML Statistician will follow the established globally-consistent methodology, but is expected to have a high level of initiative and creativity and be able to suggest enhancements to the current methodologies where appropriate.

Requirements include a background in statistics and/or mathematics (including experience in predictive and ensemble decision tree modeling), as well as a working knowledge of SAS, R, and Python.

Key Responsibilities include:

1. Prepare and validate data. Apply quantitative and qualitative analysis methods. Perform statistical and non-statistical data exploration. Identify data quality issues and work with Technology to address them.

2. Conduct data-driven analyses and create reports. Apply alternative machine learning methods (e.g., logistic regression, ensemble modelling, or other quantitative methods) to build models and to conduct analyses. Analyze and interpret data reports, draw conclusions, and make recommendations answering specific business needs.

3. Document solutions and present results in a clear, comprehensive manner to a nontechnical audience, and draft formal documentation and reports using statistical terminology.

4. Enhance existing methodology. Review the statistics and machine-learning literature to generate new ideas, concepts, and models and to improve existing methods of obtaining and evaluating data. Escalate identified risks and sensitive areas in existing methodologies and processes.

5. Maintain an industry-leading knowledge of the tools, systems and processes available for a best-in-class AML monitoring and detection system.

Qualifications:

• Strong statistical academic background, knowledge of quantitative methods, including predictive modeling techniques.
• Advanced English level
• Experience in creating and assessing Statistical Models.
• A high degree of skill with R, SAS, and the MS Office Suite. Experience with Python, Hadoop, Hive and Spark, including Spark ML is a plus.
• Experience in reporting the results of analysis in a clearly written manner, and in presenting findings during meetings and conference calls.
• Team working experience (demonstrated team player ability required)
• An understanding of the technical requirements, and an ability to communicate with Technical Support

Desirable to have:

• An ability to manipulate data using SQL or equivalent
• Experience with data exploration and SQL programming
• Experience with the Mantas (or alternative) AML monitoring system
• Knowledge of the local/regional laws and regulations applicable to anti-money laundering
• Previous experience with a financial services company (retail banking, small business banking, commercial banking, etc.)

Skills:

• Initiative, creativity, attention to detail, and basic problem-solving skills
• Statistical/data analytical skills—including the calculation and interpretation of outcomes
• Facility in working with SAS, R, and Python
• Ability to work with analytical toolsets that interact with the Hadoop ecosystem
• Ability to develop solutions using Python as the primary programming language
• Ability to work under the close supervision of a functional team manager, while preserving independence of thinking and responsibility for results
• Ability to discuss the rationale behind a critical assessment of facts and opinions, and to provide comprehensive answers and arguments
• Ability to engage in conceptual and creative out-of-the-box thinking
• Demonstrated ability to communicate effectively, both orally and in writing, with all levels of the organization and across different business units
• Self-motivation and a strong high desire for self-development and learning
• Ability to coordinate with other members of the team and to deal with conflicting time demands
• Ability to work non-standard business hours, including weekends and holidays, if necessary, as determined by business needs.

Competencies:

• Very good formal written and oral communication style
• Ability to express thoughts and concepts clearly
• Advanced statistical analysis

Teamwork:

• Ability to work well with a variety of people and to show a team-player attitude regardless the scope of responsibilities

Creativity:

• Provide input on the innovation and application of new and enhanced approaches. Have initiative and a proactive attitude.

Academic Qualifications:

• Bachelor’s university degree is required
• Master’s degree in statistics, mathematics, or related quantitative field is preferred.

Time Type:

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