Senior Data Scientist - Graphs & Entity Resolution

About the Role

Manipulation and fraud rarely happen through a single account. The hard problem in surveillance is connecting activity that's deliberately spread across many accounts, wallets, or identities that share no obvious link. You'll own the graph and entity-resolution side of the system: turning trading, account, and on-chain data into networks, resolving many identities to a single actor, and detecting the coordinated rings and collusive clusters that individual-account models miss. The second seat carries this to the DeFi venue, where entity resolution is not one capability among many but the identity substrate itself: the fusion of commercial blockchain attribution with on-chain behavioral clustering that replaces KYC on a pseudonymous exchange.

Responsibilities

• Build and maintain the entity graph that links accounts, counterparties, wallets, and behavior into a single picture of who is really acting
• Develop entity-resolution and clustering methods that stay stable over time, so the same actor is recognized as they resurface
• Detect coordinated behavior and collusion rings — including cases with no explicit shared identity; on the DeFi side, wallet-farming and sybil detection as direct outputs of entity resolution
• (DeFi seat) Co-own the Attribution Substrate: fusing vendor attribution clusters (e.g., Chainalysis) with on-chain behavioral clustering into a confidence-scored entity-resolution layer
• Build graph-based features and representations (embeddings, network features) that feed the wider detection system
• Partner with engineering as the graph extends to new data sources and market types

Requirements

• Strong applied graph ML experience: graph representation learning, embeddings, and/or GNNs on large-scale graphs
• Entity resolution / record linkage at scale, ideally with an eye to cluster stability over time
• Community and cluster detection, both embedding-based and classical approaches
• A track record detecting coordinated or collusive behavior — fraud, integrity, AML, or coordinated-campaign work all translate well
• Production ML experience: you've built graph pipelines that run, not just research notebooks
• Financial-crime, market-surveillance, or trading-domain exposure a plus
• FIX / market-microstructure fluency a plus; for the second seat, on-chain / EVM primitives and wallet-clustering experience strongly preferred

Compensation

• Base pay: $190,000–290,000
• Bonus provided as part of compensation package
• Full range of medical, financial, and other benefits

Location

This is an onsite position based out of our Santa Monica, CA or New York, NY offices.