Description

You will design, build, and implement decision-intelligence solutions to detect and prevent financial crime risks.

This role is hybrid.

Responsibilities

• Design and implement Quantexa-based AML/KYC/Fraud solutions using entity resolution, rules, scoring, and graph analytics.
• Develop detection logic aligned with financial crime typologies such as layering, mule networks, and sanctions evasion.
• Build Spark-based ingestion pipelines for customer, account, transaction, and external intelligence data.
• Model entities and relationships to support risk-based network views within Quantexa.
• Configure and tune Entity Resolution rules, scoring models, and alerting logic for contextual monitoring.

Required Skills

• 8+ years of professional experience in a relevant technical role.
• Strong proficiency in Scala or Java.
• Hands-on experience with Apache Spark and Big Data ecosystems (Hadoop, Hive, HDFS, Parquet).
• Solid understanding of entity resolution, network analysis, and graph-based data models.
• Proficiency in SQL for data validation and quality analysis.
• Experience integrating APIs, microservices, and ETL/ELT pipelines.
• Familiarity with AML and fraud typologies (e.g., structuring, sanctions circumvention).
• Experience working with cloud platforms (Azure/AWS/GCP).
• Ability to translate complex financial crime risk requirements into technical specifications.

Preferred Skills

• Experience with the Quantexa Decision Intelligence Platform.
• Knowledge of Docker or Kubernetes.

Key Skills

Education

Any Graduate