Head of Fraud & Risk Data Science
SardineFull Time
Senior (5 to 8 years)
Key technologies and capabilities for this role
Common questions about this position
Yes, this is a remote, US-based role.
The role utilizes Python 3, PostgreSQL, and AWS infrastructure including EC2, S3, RDS, and Redshift.
This information is not specified in the job description.
You will start by directly managing 2-3 data scientists and grow the team to 5-6.
Strong candidates should have full-stack data science skills including model development, analysis, production code writing, technical leadership, mentoring, and deep domain knowledge in fraud detection.
Machine learning solutions for identity fraud detection
SentiLink provides solutions to help financial institutions prevent identity fraud. Their main product uses machine learning models to detect fraudulent activities during the application process. By analyzing data and reviewing cases with a team of risk analysts, SentiLink offers insights that help clients make informed decisions about approving customers. What sets SentiLink apart from competitors is their ability to adapt their products to various types of fraud and customize them to meet the specific needs of each client. The goal of SentiLink is to enable financial institutions to minimize fraud losses while maintaining a positive customer experience.