Senior Data Engineer, Graph Analytics
TRM Labs provides a blockchain intelligence platform to help organizations investigate, monitor, and detect crypto and digital asset fraud and financial crime. They serve government agencies, financial institutions, and crypto businesses worldwide.
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About TRM Labs
TRM Labs provides a next-generation blockchain intelligence platform designed to investigate, monitor, and detect crypto and digital asset fraud and financial crime. The platform features extensive asset coverage, supporting over 200 million assets across more than 41 blockchains, including NFTs and DeFi protocols. It offers cross-chain analytics to trace the flow of funds seamlessly between different blockchains and utilizes over 150 risk categories, including FATF's money laundering predicate offenses, for customized risk scoring. TRM's data is built from a large, proprietary database of illicit activity combined with advanced data science. The company serves a global client base, including government agencies, financial institutions, and crypto businesses, helping them to safeguard the crypto financial system, maintain high standards for AML/CFT compliance, and build trust in digital assets.
Skills
About the Role
You will build scalable graph systems that analyze large networks of cryptocurrency transactions. You will design and implement graph algorithms that operate at multi-blockchain scale and optimize them for performance. You will leverage distributed databases and graph processors to implement real-time graph algorithms and integrate diverse data inputs. You will collaborate with data scientists, engineers, and investigators to convert research into production features, communicate complex implementation details to technical and non-technical audiences, and refine risk models that assign scores to addresses.
Requirements
- Academic background in a quantitative field such as Computer Science, Mathematics, Engineering, or Physics
- Strong knowledge of algorithm design and data structures
- Experience optimizing large-scale distributed data processing systems such as Apache Spark, Apache Hadoop, Dask, and distributed graph databases
- Experience converting academic research into production products
- Strong programming experience with Python and SQL
- Excellent communication skills for technical and non-technical audiences
- Self-motivated with ability to propose and validate solutions with minimal guidance
- Knowledgeable of basic graph theory concepts
Responsibilities
- Design and implement graph algorithms that analyze large cryptocurrency transaction networks
- Research graph-native technology and evaluate its benefit to data teams
- Collaborate with investigators, data scientists, and engineers to define requirements and user stories
- Understand and refine risk models that assign scores to addresses
- Communicate complex implementation details to technical and non-technical audiences
- Integrate diverse data inputs from raw blockchain data to model outputs
- Leverage distributed databases and graph processors to implement real-time graph algorithms