Senior Software Engineer, Graph Analytics

TRM Labs provides blockchain analytics and AI solutions to help various sectors detect and disrupt financial crime. As a Senior Software Engineer on the Graph Analytics team, you will build scalable systems to analyze cryptocurrency transactions, collaborating with engineers and data scientists to develop critical algorithms.

Responsibilities:

• Designing and implementing graph algorithms that analyze large cryptocurrency transaction networks at multi-blockchain scale
• Researching new graph-native technology to evaluate benefit to data science and data engineering teams at TRM
• Working on a highly cross-functional team that collaborates with cryptocurrency investigators to identify key user stories and requirements for new graph algorithms and features
• Understanding and refining TRM’s risk models which analyze large networks of cryptocurrency transactions to assign risk scores to addresses
• Communicating complex implementation details to a variety of audiences from investigators and customer success stakeholders to data engineers and data scientists
• Integrating with a diverse set of data inputs ranging from raw blockchain data to complex model outputs

Requirements:

• Your academic background is in a quantitative field such as Computer Science, Mathematics, Engineering, or Physics
• You have strong knowledge of algorithm design and data structures, and have experience applying this knowledge towards real-world problems
• You have experience optimizing large-scale distributed data processing systems such as Apache Spark, Apache Hadoop, Dask, and distributed graph databases
• You have experience converting academic research into products and have worked with research teams that regularly ship new features
• You have strong programming experience with Python and SQL
• You are an excellent communicator who is skilled at tailoring explanations of complex topics to both technical and non-technical audiences
• You are self-motivated. You propose and validate solutions with minimal guidance. You're comfortable working with ambiguity and shaping your own research direction while being accountable for outcomes
• You are knowledgeable of basic graph theory concepts