Data Scientist - AML

Description

We are

Cross River is a highly profitable, fast-growing financial technology company powering the future of financial services. Our comprehensive suite of innovative and scalable embedded payments, cards, and lending products deliver financial services for millions of businesses and consumers around the globe. Cross River is backed by leading investors and serves the world’s most essential fintech and technology companies. Together with its partners, Cross River is reshaping global finance and financial inclusion.

We are on a mission to build the infrastructure that propels access, inclusion, and the democratization of financial services. While our company has tripled in size over the last three years, our strong sense of purpose led Cross River to be named to American Banker’s list of Best Places to Work in Fintech for the last 6 years. The reason for this success is simple – our nimble and collaborative family culture lives in every member of our growing team. Together we are at the forefront of technology and innovation, and we invite passionate, collaborative, and motivated high performers to join our expanding team.

You Are

We are the Data Science team, focused on regulatory compliance. Our work primarily focuses on Fair Lending and Anti Money Laundering by assisting the relevant teams with detailed analysis and/or machine learning models. Our team is working with vital analytics to ensure we are within the guidelines for banking regulations. Our team uses SAS, Python and various machine learning algorithms to provide on-demand analysis.

You are detail oriented with an analytical, logical way of thinking, and are passionate about making data driven decisions.

This is an open role for a new member of the AML Data Science team responsible for performing analysis on data focused on Anti-Money Laundering (AML/CFT), interpreting results and developing actionable insights to accelerate operational excellence and demonstrate compliance.

You will

• Present data and analysis in a clear and concise manner allowing the audience to quickly understand the results and recommendations so they can make informed data driven decisions.
• Collaborate with various partners to provide a holistic view of the analysis. Measure and monitor results of applied recommendations and present adjustments.
• Develop scenarios involving tuning, calibration, segmentation and optimization.
• Provide routine and ad hoc reporting tied to AML/CFT compliance.
• Develop insightful and compelling summary reporting and dashboards for management and business line partners.
• Support the development of policies and procedures for AML transaction monitoring life cycle, including reviews of scenario validation, segmentation and optimization tools.
  
  

• Native level English both written and verbal, sufficient for achieving consensus and success in a remote and largely asynchronous work environment and good Hebrew
• Significant experience in implementing an end-to-end AML/CFT compliance management platform that includes transaction monitoring tools - Must
• 3+ years or relevant experience in the data analytics and/or data science field - Must
• 3+ years' experience using SQL/Python for querying data and for data manipulation / transformation - Must
• Experience implementing AML or Fraud Transaction Monitoring in Palantir, a strong advantage
• Experience in Business Intelligence/Data Exploration and Visualization tools
• Experience in Implementing AML or Fraud Solutions, AML/Fraud Alert Generation Process, Scenario Management
• Strong analytic skills and problem solving with the ability to extract, collect, organize, analyze and interpret trends or patterns in complex data sets
• Knowledge and understanding of machine learning and artificial intelligence approaches, ideally with experience of applying them in an AML/Fraud context
• Excellent computer skills, including proven experience with Microsoft Office suite
• Quick thinker, fast learner and problem solver with ability to get things done, from start to end
• Good team player, self-motivated and proactive at work
• Effective interpersonal, verbal, and written communication skills