We are
The Data Science team, focused on Risk Management, our work is centered around compliance and due diligence, specifically Fair Lending and Anti Money Laundering by unmasking the bad guys and solving problems. Our team is working with vital analytics to ensure we are within the guidelines for banking regulations, managing the bank's exposure to loss and risk. Our team uses SAS, Python and various machine learning models to provide on-demand analysis.
You will
Manage a team that will design, develop, and implement predictive models, machine learning algorithms, and statistical techniques to assess fair lending risks and detect potential instances of discrimination
Analyze large datasets and identify patterns, trends, and potential areas of concern related to Fair Lending practices
Utilize advanced statistical methods to evaluate model performance, including model calibration, validation, and interpretation of results
Collaborate with cross-functional teams to understand business requirements and develop data-driven solutions for Fair Lending compliance
Develop and maintain of scalable data pipelines, data models, and analytical tools to support fair lending analysis and reporting activities
Be committed to diversity, equity, and inclusion, with a passion for promoting fairness and equality in lending practices
This position reports to the Fair Lending Data Science Manager
You have
A Bonus
Why join us
Cross River Technologies develops software infrastructure for the fintech industry. Providing innovative technological solutions for various financial services, including payments, credit cards, and loans.
Globally, Cross River has 900 employees, 170 of whom are based in the R&D center at the Jerusalem offices.
We offer a wide range of wellness benefits including ongoing learning and development opportunities; monthly wellness reimbursement; volunteering opportunities; charitable donation matching; Keren Hishtalmut on full salary; private health and dental insurance; advanced study fund and various company events.
We place a strong emphasis on employee satisfaction and growth.