SoFi is looking to architect and build sophisticated fraud detection and anti-money laundering solutions using cutting-edge technologies and data-driven approaches to protect its members and business.
Requirements
- Expert-level proficiency in languages suitable for high-performance financial systems.
- Deep experience with Apache Kafka, Apache Flink, and real-time event processing architectures.
- Hands-on experience with AWS SageMaker, Feature Store, and ML model deployment frameworks.
- Expertise in Snowflake, AWS DynamoDB, and time-series databases for fraud analytics.
- Experience with AWS Neptune and Gremlin for relationship analysis and investigation workflows.
- Experience with rule engines like Flowable, Camunda, or similar decisioning platforms.
- Proficiency with Apache Druid or similar OLAP systems for operational analytics.
Responsibilities
- Real-time Fraud Detection: Design and implement advanced fraud detection systems using machine learning models, real-time streaming analytics, and complex event processing.
- AML Compliance Solutions: Build comprehensive anti-money laundering solutions including transaction monitoring, customer due diligence (CDD), and suspicious activity reporting systems.
- Data-Driven Risk Models: Develop sophisticated risk scoring models leveraging Member360 unified data layer and advanced analytics capabilities.
- Streaming Data Architecture: Build real-time data pipelines using Apache Kafka, Apache Flink, and AWS Kinesis for processing high-volume transaction streams.
- Machine Learning Integration: Implement ML models using AWS SageMaker, Feature Store, and the Batch Inference Framework for fraud and AML detection.
- Graph Analytics: Develop entity relationship analysis using AWS Neptune for investigating complex fraud patterns and money laundering networks.
- Real-time Analytics: Build operational dashboards and investigative tools using Apache Druid for seconds-fresh fraud and AML analytics.
Other
- The position is based in Seattle or San Francisco and reports to the Director of Fraud Engineering within the FROST organization, focusing on solution delivery.
- Extensive experience building fraud detection or AML solutions in financial services
- Proven track record with real-time data processing, machine learning, and high-scale distributed systems
- Deep understanding of financial crime patterns and regulatory requirements.
- Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
