Senior Software Engineer Graph Analytics

Skills

About the Role

You will build scalable graph systems that analyze large networks of cryptocurrency transactions. You will collaborate with engineers, data scientists, and investigators to design mission-critical graph algorithms that analyze flows of funds. You will leverage distributed databases and graph processors to implement real-time graph algorithms at the multi-blockchain scale. You will collaborate with data science teams to identify opportunities to apply tools and techniques from graph theory to a variety of predictive learning problems.

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.

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