Data Scientist – Blockchain Intelligence

Job not on LinkedIn

🕒 June 16

🗽 New York – Remote

🗽 New York – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 51%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Merkle Science

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

⚖️ Legal

📋 Compliance

Consulting • Legal • Compliance

Merkle Science is a next generation predictive cryptocurrency risk and intelligence platform founded in 2018, focusing on helping crypto companies, financial institutions, and government entities detect, investigate, and prevent illegal activities involving cryptocurrencies. Their proprietary Behavioral Rule Engine enables compliance teams to meet KYC/AML obligations and navigate the complexities of illicit activities in the cryptocurrency space. Merkle Science aims to create infrastructure for the safe growth of the cryptocurrency industry within the larger financial services ecosystem.

📋 Description

• Turn raw on-chain activity into trustworthy intelligence • Design, test, and ship clustering and attribution heuristics • Own your data end to end • Build and maintain the pipelines that take a heuristic from notebook to production • Investigate edge cases and translate findings into repeatable logic • Partner with investigations and product to define what 'correct' looks like

🎯 Requirements

• 4+ years building data science or data engineering systems that actually shipped (not just notebooks) • Strong Python and SQL; comfortable with large datasets and the gotchas of joins, dedup, and skew at scale • Solid grasp of clustering, graph/network analysis, or entity resolution • Ability to reason about precision vs. coverage trade-offs and defend your metrics • Self-directed: you can scope an ambiguous problem, get the data yourself, and drive it to a result

🏖️ Benefits

• Excellent health insurance • Flexible time off • Learning & development initiatives • Team-building sessions • Discussions around mental health • Industry-leading compensation • Generous equity