AML Statistician

Citigroup Inc. is a leading global financial services company that offers a wide range of financial products and services to individuals, corporations, governments, and institutions.

The AML Statistician will work under the supervision of a Functional Team Manager to provide statistical analyses and reports to support the development of effective anti-money laundering (AML) monitoring systems.

The scope of these analyses will cover all aspects of the work performed by IV across various Citi AML activities, including optimization, segmentation, tactical tuning, KYC, etc., depending on current needs and project plans.

Key Responsibilities:

* 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.

* Conduct data-driven analyses and create reports, apply alternative machine learning methods, build models, conduct analyses, analyze and interpret data reports, draw conclusions, and make recommendations answering specific business needs.

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

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

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

Salary Range: $87,280.00 - $130,920.00 per annum

Job Requirements:

• Strong academic background in statistics or mathematics, knowledge of quantitative methods, predictive modeling techniques
• Experience in creating and assessing statistical models, skill with R, SAS, MS Office Suite, Python, Hadoop, Hive, Spark
• Ability to communicate complex analytical concepts in simple terms, team working experience, initiative, creativity, attention to detail, basic problem-solving skills
• Facility in working with analytical toolsets interacting with Hadoop ecosystem, ability to develop solutions using Python as primary programming language