AML/Fraud Analyst focusing on transaction monitoring to mitigate financial risks at Swan, Europe’s embedded banking specialist.
About the role
- Lead Risk Architect for Financial Crime Platform responsible for designing detection systems and analytics. Involved in data integration, risk detection, and collaboration across teams.
Responsibilities
- We’re looking for a Lead Risk Technology Architect with a Non-Financial Risk background to join our Financial Crime team.
- You’ll be part of the group responsible for designing, building and maintaining high-performance AML & fraud detection systems, entity resolution, and compliance analytics across Tyme’s ecosystem.
- The goal of the Financial Crime Platform is to reduce friction, improve outcomes for genuine customers, reduce costs and reduce vendor dependency, by architecting a unified non-siloed platform across Fraud and Financial Crime for the whole Tyme Group entities.
- You’ll work with large, complex transactions, customer behaviour and apply models and decisioning frameworks in Databricks, integrate data from multiple systems in real time and batch, and help design the data foundation for real-time risk detection and case management.
- Demonstrated experience in multiple forms of data ingestion, event-based streaming, synchronous real time ingestion approaches.
- Architect our SLM (localized LLM) strategy.
- Use the above as the basis for building a low cost, but high performance multi-agent AI architecture with the ability to create an ontology via knowledge graphs.
- Design the ODS LDM and the Star/Snowflake LDM to support knowledge storing, sharing, audit and re-use for Agentic AI to store, forward, capture knowledge and decisions made.
- Apply entity resolution techniques in place, without further data movement.
- Be a proponent of not moving large scale data movement to multiple data sinks, process data in place rather than move data to different sinks.
- Be a proponent of the SHIFT LEFT paradigm and be a Data Foundation proponent.
- Utilize tooling that allows SHIFT LEFT, for example instead of a physical Graph Database, a virtual Graph Database sitting on top of a solid Data Foundation.
- Understand real time scaling and performance needs for fast track processing, near real time and slow track batch oriented needs and which types of Compute, GPU and storage to apply and appropriate Notebook technologies (Scala, PySpark, Python, SQL).
- Understand how to construct and deploy natively or via third party LLMOps and MLOps and how a comprehensive Data & AI monitoring strategy can be put into place.
- Be a proponent of Governance, Lineage, Auditability, Data As A Product (Data Contracts) via utilizing the power of the Unity Catalog across the entire architecture.
- Design systems to lower cost, require less IT support and to be adaptable/flexible.
- Collaborate closely with Data Scientists, Analysts, Compliance, Operations and our Product/Feature teams to operationalize models and rules.
- Integrate with external systems (e.g. sanctions, ID&V, biometrics and authentication systems) to enrich risk and identity data by building a rich profiling layer capable of supporting detection and investigation. Profiling for sub-millisecond needs in fraud detection architecturally and for slower profiling for investigations.
Requirements
- Bachelor’s degree or above - ideally in Computer Science with specialization in Data Architecture/AI.
- 10-15 years of experience, preference in Financial Services, Fast Moving E-Commerce industries.
- Held the position of Lead Risk Architect at one of the above industries with a suitable size customer base and designed global/multi-country systems.
- Hands on experience demonstrating architecture, design and implementation of Financial Crime or Cyber Security detection systems using Databricks, Snowflake, GCP Big Query/Table and/or Cloudera type systems. Systems designed on other architectural or older architectural paradigms are not what we are looking for, but a migration of knowledge from these to modern systems is critical.
- Experience working with structured and unstructured data in a production environment.
- Secure Coding practices – testing/QA in Spark, Python, PySpark, PostGreSQL, Databricks SQL.
- Comfortable with cloud-based platforms (preferably AWS, but good data engineering on GCP is also welcomed).
- Good communication skills in English — able to collaborate with cross-functional teams in an international environment.
- Proficiency in working with Text, Delta, Parquet, Iceberg/S3, JSON, CSV, and XML data formats.
- Working knowledge of Kafka/MQ/Spark structured real time streaming.
- Solid understanding of git-based version control, DevOps, and CI/CD.
- Experience of working on Atlassian stack.
- Knowledge of common web API frameworks and web services.
- Strong teamwork, relationship, and client management skills, and the ability to influence peers and senior management to accomplish team goals.
- Willingness to embrace modern technology, best practice, and ways of work.
- Preference for Databricks/Snowflake/GCP Data certification at several levels in Data Engineering, Gen AI, Data Architecture.
- Experience with Agentic AI, MLFlow, Judge Based Eval Models.
- Experience with building LLMs, RAG and other approaches, with mastery in prompt engineering.
- Familiarity with Entity Resolution frameworks (e.g., Quantexa, Senzing, open source Entity Resolution tools).
- Experience with data streaming frameworks (Kafka, Spark Streaming, MQ).
- Experience with Regulatory Model Validation against AI
Benefits
- Be part of a mission-driven team tackling real-world financial crime problems.
- Work with modern data tech stack with Agentic AI and advanced ML.
- Hybrid working model with flexible hours.
- International and collaborative culture — working with colleagues across Vietnam, Singapore, Philippines and South Africa.
- Competitive salary, performance bonuses, and learning support.
Job title
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