Int. Data Scientist to conduct all analytical activities related to AML transaction monitoring systems for a large financial bank - 45735

Job ID:  45735
# of positions: 1
Duration:  12 months
Extension possible: Yes
Conversion Possible:  Based on availability
Interview Process: 2 rounds of Webex
Location:  HYBRID (flexible on going in for specific reasons/ keep candidates within commuting)



Job Description

• Reporting to the Senior Advanced Analytics Manager, the Data Scientist I will be conducting all analytical activities related to AML transaction monitoring systems.
• Provide maintenance of transaction monitoring scenarios, and analytical queries in support of the bank's strategic efforts to mitigate money laundering and terrorist financing risk
• Conduct activities related to AML/ATF scenario performance review and tuning
• Help maintain a structured documentation process to demonstrate an effective scenario review program to satisfy audit, compliance, and regulatory requirements
• With assistance from management, assist with scenario related issues/questions from Global AML members, audit, and other partners
• Provide solutions where there is a need for advanced quantitative, statistical, and analytical skills
• Undertake ad hoc data mining research projects to find hidden patterns and potential anomalies within data
• Partner with GAML teams to implement changes to existing solutions and/or the implementation of alternative solutions
• Use statistical and data mining techniques to build and maintain effective and efficient transaction monitoring, customer behavior, and risk scoring machine-learning models
• Communicate results to various stakeholders and ensure they fully understand implications of relevant measures

 
Must Have:

• Expert knowledge of SAS, SQL, & Python are essential.
• Ability to apply statistical techniques and data mining tools to solve business problem.
• Minimum 1 year of experience in data modeling/machine learning.
• Experience in query optimization, debugging and automation.
• Strong knowledge of Microsoft Office suite, including Excel and PowerPoint.

•       Master’s degree or higher in Statistics, Computer Science/Software Engineering